Lecture 7 – Linear Models

# Lecture 7 – Linear Models
## STAT/BIOF/GSAT 540: Statistical Methods for High Dimensional Biology
### Keegan Korthauer
### 2020/01/27 Slides by: Gabriela Cohen Freue with contributions from Jenny Bryan and Keegan Korthauer

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<big>

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# Recall from last class...

<big>

### 1. show how to compare means of different groups (2 or more) using a linear regression model

- dummy variables to model the levels of a qualitative explanatory variable

### 2. write a linear model using matrix notation

- understand which matrix is built by R
  
### 3. distinguish between single and multiple hypotheses 
  - `$t$`-tests vs `$F$`-tests  
  
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# <center> Do we think that the expression levels at different developmental stages are generated by distributions with different location (mean)? Or a single common distribution?

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## **Quick review**: from `$t$`-test to linear regression
<big>

### **2-sample t-test**

$$
Y \sim F; \ E[Y]= \mu_Y ; \ Z \sim G; \ E[Z]= \mu_Z
$$
$$ H_0: \mu_Y = \mu_Z$$

### **Linear regression**

$$ Y = X\alpha + \epsilon; \text{ }\hspace{1em} H_0: \alpha_j = 0$$

<center>
## HOW? WHY?

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## **HOW??** : Cell means model using dummy variables

$$
Y \sim F; \ E[Y]= \mu_Y ; \ Z \sim G; \ E[Z]= \mu_Z
$$
<center>**↓**

`$$Y_{ij}= \mu_1 x_{ij1} + \mu_2 x_{ij2} + \varepsilon_{ij}; \ i=1, \dots, n; \ j={1,2}$$`
`$$x_{ij1}=\bigg\{\begin{array}{l} 
1\text{ if } j=1\\
0 \text{ otherwise}\\
\end{array}, \hspace{1em} x_{ij2}=\bigg\{\begin{array}{l} 
1\text{ if } j=2\\
0 \text{ otherwise}\\
\end{array}$$`

<center>**↓**

]

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width="300" />
]

---

## **HOW??** : Changing the parametrization to reference-treatment using dummy variables

$$
Y \sim F; \ E[Y]= \mu_Y ; \ Z \sim G; \ E[Z]= \mu_Z
$$
<center>**↓**

`$$Y_{ij}=\theta+ \tau_1 x_{ij1} + \tau_2 x_{ij2} + \varepsilon_{ij}; \ i=1, \dots, n; \ j={1,2}; \tau_1=0$$`
`$$x_{ij1}=\bigg\{\begin{array}{l} 
1\text{ if } j=1\\
0 \text{ otherwise}\\
\end{array}, \hspace{1em} x_{ij2}=\bigg\{\begin{array}{l} 
1\text{ if } j=2\\
0 \text{ otherwise}\\
\end{array}$$`

<center>**↓**

.pull-left[
 
 
 
`$$\begin{array}{l}
E[Y_{i1}] &= \theta=\mu_1 \\
E[Y_{i2}] &= \theta + \tau_2=\mu_1\ + (\mu_2 - \mu_1) = \mu_2
\end{array}$$`

]

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<img 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" width="150" />
]

---

## **HOW??** : Changing the parametrization and using dummy variables

$$
Y \sim F; \ E[Y]= \mu_Y ; \ Z \sim G; \ E[Z]= \mu_Z
$$
<center>**↓**

`$$Y_{ij}=\theta+ \tau_2 x_{ij2} + \varepsilon_{ij}; \ i=1, \dots, n; \ j={1,2}$$`
`$$x_{ij2}=\bigg\{\begin{array}{l} 
1\text{ if } j=2\\
0 \text{ otherwise}\\
\end{array}$$`

<center>**↓**

.pull-left[
 
 
 
`$$\begin{array}{l}
E[Y_{i1}] &= \theta=\mu_1 \\
E[Y_{i2}] &= \theta + \tau_2=\mu_1\ + (\mu_2 - \mu_1) = \mu_2
\end{array}$$`

]

---

## **Using matrix notation ...**

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<img 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" width="600" />
]
.pull-right[

* `$x_{ij2}$` is the second column of design matrix `$X$`

* `$x_{112} = 0$` and `$x_{122} = 1$`

Red
`$$Y_{11} = 1*\theta + 0*\tau_2 + \epsilon_{11} =\theta + \epsilon_{11}$$`

Blue
`$$Y_{12} = 1*\theta + 1*\tau_2 + \epsilon_{12} = \theta + \tau_2 + \epsilon_{12}$$`
* Tip: examine design matrix in R with `model.matrix()`

]

### ... and similarly beyond 2 group comparisons (ANOVA)

---
class: center

---

# **Parametrizations**

## Different ways of writing this [design matrix, parameter vector] pair correspond to different parametrizations of the model
# `$$Y = [X\alpha] + \varepsilon$$`
 <big>
 Understanding these concepts makes it easier ...
- to interpret fitted models
- to fit models such that comparisons you care most about are directly addressed in the inferential "report"
---

## For example: comparisons of mean expression levels between groups!
<center>
<img 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width="500" />
</center>
By default, `lm` estimates group mean differences (with respect to a reference group):

```r
summary(lm(gExp~devStage,subset(devDat,gene=="geneB")))$coeff
```

```
##                  Estimate Std. Error   t value     Pr(>|t|)
## (Intercept)     5.5408571  0.1021381 54.248698 1.307554e-34
## devStageP2      0.3040179  0.1398583  2.173756 3.678022e-02
## devStageP6      0.2433929  0.1398583  1.740282 9.085489e-02
## devStageP10     0.8342679  0.1398583  5.965093 9.559065e-07
## devStage4_weeks 3.6325179  0.1398583 25.972843 5.266481e-24
```
---

# We can tell R to use the cell-means parametrization

Write the formula as `Y ~ 0 + x` in the `lm` call to remove the intercept `$(\theta)$` parameter and fit cell means parameters instead.

```r
summary(lm(gExp~0+devStage,subset(devDat,gene=="geneB")))$coeff
```

```
##                 Estimate Std. Error  t value     Pr(>|t|)
## devStageE16     5.540857 0.10213807 54.24870 1.307554e-34
## devStageP2      5.844875 0.09554141 61.17635 2.287666e-36
## devStageP6      5.784250 0.09554141 60.54181 3.250790e-36
## devStageP10     6.375125 0.09554141 66.72630 1.223052e-37
## devStage4_weeks 9.173375 0.09554141 96.01465 5.523959e-43
```

Now, the *t*-test column of the output represents the test of whether each group mean is equal to zero

---

## Recall that we can obtain one set of parameters from the other!

---

# Today... more complex models

### 1. more than one factor with multiple levels

- how to model many categorical variables and their interaction

### 2. distinguish between simple and main effects 
  - `lm` vs `anova` tests
  
### 3. nested models 
  - `$t$`-tests vs `$F$`-tests  
  
### 4. continuous explanatory variables

- the regression line

---

## Increasing the complexity of the linear model ...

### What if you have *two* categorical variables?

e.g., `gType` and `devStage` (for simplicity, let's consider only E16 and 4W)

- ANOVA is usually used to study models with one or more categorical variables (factors)

- Can we combine levels into 4 groups to simplify the analysis??

---

## Two-way ANOVA or a linear model with interaction

Which group means are we comparing in a model with 2 factors?

`$$\mu_1=E[Y_{(wt,E16)}], \ \mu_2=E[Y_{(NrlKO,E16)}], 
\ \mu_3=E[Y_{(wt,4W)}], \ \mu_4=E[Y_{(NrlKO,4W)}]$$`

---

# Reference-treatment effect parametrization

<big>

* By default, `lm` assumes a **reference-treatment effect** parametrization

* Mathematically, we need *more* dummy variables, see [math handout](source/SupportingMaterial/math_handout.html) for more details

```r
twoFactFit <- lm(gExp ~ gType * devStage, twoDat)
```

```
##                              Estimate Std. Error   t value     Pr(>|t|)
## (Intercept)                 9.9080000  0.1574912 62.911469 2.027211e-15
## gTypeNrlKO                 -0.9856667  0.2405717 -4.097184 1.767824e-03
## devStage4_weeks             1.6345000  0.2227261  7.338609 1.469261e-05
## gTypeNrlKO:devStage4_weeks -2.0380833  0.3278440 -6.216626 6.560671e-05
```

---

## Cell-means and treatment effects in the two-way model - why do we need more dummy variables?

```r
table(twoDat$grp)
```

```
## 
##        wt.E16     NrlKO.E16    wt.4_weeks NrlKO.4_weeks 
##             4             3             4             4
```

```r
(means.2Fact <- as.data.frame(twoDat %>% 
 group_by(grp) %>% 
 summarize(cellMeans=mean(gExp))) %>%
 mutate(txEffects=cellMeans-cellMeans[1],
 lmEst=summary(twoFactFit)$coeff[,1]))
```

```
##             grp cellMeans  txEffects      lmEst
## 1        wt.E16  9.908000  0.0000000  9.9080000
## 2     NrlKO.E16  8.922333 -0.9856667 -0.9856667
## 3    wt.4_weeks 11.542500  1.6345000  1.6345000
*## 4 NrlKO.4_weeks  8.518750 -1.3892500 -2.0380833
```

---

# What is the reference group here?

As before, comparisons are relative to a reference but in this case there is a reference level *in each factor*: wt and E16

---

# The reference: wt & E16

**Mean of reference group**: `$\theta=E[Y_{wt,E16}]$` 
  
**`lm` estimate**: `$\hat{\theta}$` is the sample mean of the group

```
##                              Estimate Std. Error   t value     Pr(>|t|)
*## (Intercept)                 9.9080000  0.1574912 62.911469 2.027211e-15
## gTypeNrlKO                 -0.9856667  0.2405717 -4.097184 1.767824e-03
## devStage4_weeks             1.6345000  0.2227261  7.338609 1.469261e-05
## gTypeNrlKO:devStage4_weeks -2.0380833  0.3278440 -6.216626 6.560671e-05
```

```
##             grp cellMeans  txEffects      lmEst
*## 1        wt.E16  9.908000  0.0000000  9.9080000
## 2     NrlKO.E16  8.922333 -0.9856667 -0.9856667
## 3    wt.4_weeks 11.542500  1.6345000  1.6345000
## 4 NrlKO.4_weeks  8.518750 -1.3892500 -2.0380833
```

In general, one is not interested in: `$H_0: \theta=0$`

---

## Simple genotype effect: wt *vs* NrlKO at E16

<big>
And now the "treatment effects"...

> **Important**: effects are not marginal but *conditional* effects (at a given level of the other factor, e.g., at E16), usually called **simple effects**

---

## Simple genotype effect: wt *vs* NrlKO at E16

**Effect of genotype at E16**: `$\tau_{KO}=E[Y_{NrlKO,E16}]-E[Y_{wt,E16}]$`

**`lm` estimate**: `$\hat{\tau}_{KO}$` is the *difference* of sample respective means (check below)

```
##                              Estimate Std. Error   t value     Pr(>|t|)
## (Intercept)                 9.9080000  0.1574912 62.911469 2.027211e-15
*## gTypeNrlKO                 -0.9856667  0.2405717 -4.097184 1.767824e-03
## devStage4_weeks             1.6345000  0.2227261  7.338609 1.469261e-05
## gTypeNrlKO:devStage4_weeks -2.0380833  0.3278440 -6.216626 6.560671e-05
```

```
##             grp cellMeans  txEffects      lmEst
## 1        wt.E16  9.908000  0.0000000  9.9080000
*## 2     NrlKO.E16  8.922333 -0.9856667 -0.9856667
## 3    wt.4_weeks 11.542500  1.6345000  1.6345000
## 4 NrlKO.4_weeks  8.518750 -1.3892500 -2.0380833
```

**But**, do you want to test the *conditional* effect at E16: `$H_0: \tau_{KO}=0$`??

---

## Simple developmental effect: E16 *vs* 4W in wt

<big>

Similarly, for the other factor:

---

## Simple developmental effect: E16 *vs* 4W at wt

**Effect of development in wt**: `$\tau_{4W}=E[Y_{wt,4W}]-E[Y_{wt,E16}]$`

**`lm` estimate**: `$\hat{\tau}_{4W}$` is the *difference* of respective sample means (check below)

```
##                              Estimate Std. Error   t value     Pr(>|t|)
## (Intercept)                 9.9080000  0.1574912 62.911469 2.027211e-15
## gTypeNrlKO                 -0.9856667  0.2405717 -4.097184 1.767824e-03
*## devStage4_weeks             1.6345000  0.2227261  7.338609 1.469261e-05
## gTypeNrlKO:devStage4_weeks -2.0380833  0.3278440 -6.216626 6.560671e-05
```

```
##             grp cellMeans  txEffects      lmEst
## 1        wt.E16  9.908000  0.0000000  9.9080000
## 2     NrlKO.E16  8.922333 -0.9856667 -0.9856667
*## 3    wt.4_weeks 11.542500  1.6345000  1.6345000
## 4 NrlKO.4_weeks  8.518750 -1.3892500 -2.0380833
```

---

# Interaction effect

Is the effect of genotype the same at different developmental stages? (or is the development effect the same for both genotypes?)

**Yes if**, there's no interaction effect, i.e., `$\tau_{KO4W}=0$`

The genotype effect at E16 is `$\tau_{KO}$`. However, `$\tau_{KO}$` does not seem to be the effect at 4W. The difference is the interaction effect!
---
## Interaction effect

`$\tau_{KO4W}=(E[Y_{NrlKO,4W}]-E[Y_{wt,4W}])-(E[Y_{NrlKO,E16}]-E[Y_{wt,E16}])$`

```
##                              Estimate Std. Error   t value     Pr(>|t|)
## (Intercept)                 9.9080000  0.1574912 62.911469 2.027211e-15
## gTypeNrlKO                 -0.9856667  0.2405717 -4.097184 1.767824e-03
## devStage4_weeks             1.6345000  0.2227261  7.338609 1.469261e-05
*## gTypeNrlKO:devStage4_weeks -2.0380833  0.3278440 -6.216626 6.560671e-05
```

```r
means.2Fact
```

```r
((means.2Fact$cellMeans[4]-means.2Fact$cellMeans[3])-
    (means.2Fact$cellMeans[2]-means.2Fact$cellMeans[1]))
```

```
## [1] -2.038083
```

---

## Summary of model parameters: with interaction

model parameter | R estimate| stats | interpretation
--------|---------|---------
`$\theta$` | (Intercept) | `$E[Y_{wt,E16}]$` | reference
`$\tau_{KO}$` | gTypeNrlKO | `$E[Y_{NrlKO,E16}] - E[Y_{wt,E16}]$` | *conditional* effect of NrlKO *at* E16
`$\tau_{4W}$` | devStage4_weeks | `$E[Y_{wt,4W}] - E[Y_{wt,E16}]$` | *conditional* effect of 4W *at* wt
`$\tau_{KO4W}$` | gTypeNrlKO: devStage4_weeks | `$E[Y_{NrlKO,4W}] - E[Y_{wt,4W}] - \tau_{KO}$`  | *interaction* effect of NrlKO and 4W

It is *important* to remember that `lm` reports *simple, not main* effects!! why?? because of the parametrization used!! (see see [math handout](source/SupportingMaterial/math_handout.html))

It can also be shown that `$\tau_{KO4W}=E[Y_{NrlKO,4W}]-\tau_{4W}-\tau_{KO}-\theta$` (see previous slide)

---
class: middle

### Let's examine these parameters closer and some examples

<big> 
For our model, `lm` tests 4 hypotheses:

.pull-left[
> ### `$H_0: \theta=0$`
### `$H_0: \tau_{KO}=0$`
### `$H_0: \tau_{4W}=0$`
### `$H_0: \tau_{KO4W}=0$`
]
.pull-right[
 
<img 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PDF8KXRPeMrJnmmqWah5vYWqju4LIHlB6s+6+s7i2yO2sbake3tHQwdFZ2EnVld8C4rrp/c3rgPeNzxbEKioWh3tnc66aBPLDncN9wv3D8sIDQwJCg4ODDEL5QUtivcfY9LhEOkDcU6yi3aH7kyJ8WlxR/fm51wbl9BYmFS0f7iA8UHiw+VJjem9KVOpWEOCyLxQE5PySjN7Dz2+viPk7SnhLLUTltl+5yJzzlxtiy39Vx/3kT+j0LCec4iqWLNC2YlzqWBZfsvZpfXVNyvfFcNLvFc1qpxqaXUZV65WN/W8Pjqq2vT1783Qc00LRytIjfk2zTaDTt23LS95dTp3uVx2/GOxV3tezLdXPdx9+d6nj1oeZjfm/jIs0+rn7N/6fGzgWtPTg9GD7k+1X8m85xvmH2E7QXvS8lR7VcOr33euI+ZjSu/FZignVh/93ly/P3zD/1TD6d7PvbMPJod/PTxCzTHNi/91XjB+1vK9/rFmSXtn8Ur7KvV61Zb/pcCdyBLaBiJgHsoC9RTtDf6GyYNK4BtwjngFvAVBC8qJqrH1MeJ9jT8NHO0D+gu02czHGKMZgph9mLRYWVnXUAioZgjltOSS4DrB/cjnjLeJD4XfiUBeoEPgi1CR4QdRXhExkRLxMjiIuLvJaok90ipS6OlB2TyZEly4nKz8vUKsYqaiutKncqpKmaqeNUHahnq1hoEjXuaKVr6WqvazTrRuvK6H/Uu6nsbcBoMGR43sjBaN75qEmzKZzpodthcy/yTRdEOO0vIssHKx5rB+u7OJBtNmx+21+woyP3hi0OtY7iTjNMn5xqXMFdp1ym3Enc3D2aPAc+TXg67OHa93V3rvY9k6cPt85nc6Zvl5+kv5D8TcDUwMcgkmD54NKQ6NCHMOlww/OeeJxEVkREUJcpiVEt0UoxRLDF2OK4iPnGvS4LaPq5EVOLnpJH9tw/UHDx76FBySIpzqsFfsmk8h2kOrx+ZP/o+/XlGR+aFYynH/U6Yn5Q5xXRqLevj6dHsJ2ce5Tw82587dG44bzT/TcG7wqnzX4oWL4AS6lKOMomL2uV2FYGVB6tyq69c6r48VvOzjumKTL1FQ8DVtGvl1+83zjYztOi1pt0YbOft8L9Zc2uhS+v2X3cG7gl3J95/+cDwYf0jyb6ix+gB0pPOIcWnrc8pI+SXF197jldNDs6QFoQ2/b/9H91mwaoCcIYXyVDpAXA4A8Ax5IAQ+wIAGxUAtjQAOGoAeIcOgJkTAGTC++f8gJDEkwowAm4k21RFMmkXEAwOgmxQBW6BYTAPESFxJDckQ8lQKXQH+gBTw/KwC5wM18GvUESUDioCVYYaQdMjOdohdBt6CaOKicJcwrzBsmAtscnYG0iOpYALx9XiviC5VDz+FoFIcCdUE9aRLKmOmol6L/U40YrYQiNJU4hkOplIbnMEyWaOM7AwFDHKMLYxWTO9YaawYFnyWGVZu9hc2GbZkzk4OOo57TmXucq4bbnXeGp4vfjo+Lr4YwWkBMYEc4R2CmOF20WiRWVEp8WqxEMlFCVWJHuk8qTDZUxk+WRX5V7KtytkKnopKSpTK0+p9KjWqeWpH9VI1KRohWkH6QTpBuv561sbKBtyGgGj98gNudH0gtlx8/0WUTtCLUOs9lgn7Ey3uWDbYjdo/8WRxknG2c4lzrXYrdd9xVPGy2dX3u6nJCYfB3Ku7yt/wYCAwJqghRDN0JSw3j3sEf6RTVFU0aSYG3E88a0JXon4pJYDEYekkqdTK9LIR7iPDmYcPqZ+QuFU+OmHORa5E/lHz0sU15cKXNxb0Vj19jJzrfWV4w0j1+WaslqhtsSb6M6cO/A9r/ttD/kfHe7/9sR/6PVzj5FXo36vv46ffbfrg8z01GzU5465B1/PflP4Xrm4sST702HZbsVqVXYNvTa8fnLDbGv/gAAGEAELEAByQA/YAT+QCLIQ73eBUbAEsUDKkCMUC+VCbdBbmAArwB5wBnwD/oTiRzmjMlF30RBaH70PfQ09ixHFkDCFmBdYdqwLNhf7AseD88FV4ebxWvgj+GcEMUICYYBKiuoo1Ry1B3UPUYN4mUaQpoCWnTaXjpOumF6c/iqDAcMQYzATzFTIrME8zBLPysnazubDjme/wuHOieG8ykXmZuF+wJPMq8X7g+86f4yAqsCy4E2hw8K2Iiwio6LlYhRxAwlGifeS7VJnpaNk7GWV5Njk1uQnFDoUC5SSlEkqFqrKakLqLBrUmhgtSBvowLo4PRp9jP6ywZzhpNFL4ycmPaZdZu3mrRatO9ot71oNWI/v/G5LtBOy13JwQm4xJ52vuAy5LrsLedh4HvBq2DXlLUja7VNAfu7H4G8VcDiwK2gN8XZ8WHP4coRe5BHKULRwTFxsf7zy3oJ92ERK0vgB+4P3knVSmv9SS2s5onf0QYZr5sfjh0+qnvp4uvxM0FmVc1R5UwX959uLG0oul10qr6lsrO68/Kj22ZWRhqfX7jdeaT7W6t0m1T53s7Yz8LbZXY/uyJ70hxcf3ewfGZgfwjxjGRZ8IT2q/FpjTOMtzzvM5PyHsem+mdZPRV/i500W4G9Vi7o/7v3UX65apV4jr1/d8j8M8IAZCCFr3wr4gxRQBG6CMQiNrPqdUDSUD92GZmFW2ACOgqvgcRQPygNViBpHi6Ej0DcweIwLphKzjnXDtuB4cUdxP/Gh+LfI+h6ksqbqobamHiJ6E7/QJNNy0F6jc6BbpC9kMGdYYaxnCmWWYv7M0siawubALsEBc7zh7OZq4C7lOcd7hu8scg+5jHh1WHhG5KcYtTi/hJqkg1Sk9GmZFtkJeUYFS8VTSkMqrKpOaqfUH2qitXS043Su6s7rGxnkG/4wdjZpMuMw32cxaqltlWf908bF9rm9v8Oy0ykXUddmdxOPB15muzq85UgFZCrfJL9vAWGBH4ODQj6GhYZ/joiM/BYVF70cmxTPsff2vsgkwf1PDx5OVkuZ+Cv9sNSR7vTdGV+PJZ9gP1mfZXV6+syRs2K53Xn+BZjCkiK94hcl0WW0FysqDCpfVydd5q25VedbT2i4cs35+lpTWYtl69e2cx36Nz90nrjNcyf7Hl33sR66B2d6eR9V9is+7nhiPvjkqfOz4WHnkf6XxqPXXgu8+Wts9q37xPDk7vdTU+HTUzP2s3Wf5r7wz2nPG31VXeBf+PSt9TtlkXOx6wfpx/ul0KX5n9E/XyzrL5ev0KxErdxbpVt1WS1enVpTWNu71rU2v86zbrEes1683ru+tCG8Ybuxb6NiY3DT/1H+SopbxwdENAQA83pjY0EUAFwWAGunNjZWSjY21kqRZGMUgFuh2999ts4a5IwpWNhEDwTy//X95X8Ay7HcVWfii9YAAAIFaVRYdFhNTDpjb20uYWRvYmUueG1wAAAAAAA8eDp4bXBtZXRhIHhtbG5zOng9ImFkb2JlOm5zOm1ldGEvIiB4OnhtcHRrPSJYTVAgQ29yZSA1LjQuMCI+CiAgIDxyZGY6UkRGIHhtbG5zOnJkZj0iaHR0cDovL3d3dy53My5vcmcvMTk5OS8wMi8yMi1yZGYtc3ludGF4LW5zIyI+CiAgICAgIDxyZGY6RGVzY3JpcHRpb24gcmRmOmFib3V0PSIiCiAgICAgICAgICAgIHhtbG5zOmV4aWY9Imh0dHA6Ly9ucy5hZG9iZS5jb20vZXhpZi8xLjAvIgogICAgICAgICAgICB4bWxuczp0aWZmPSJodHRwOi8vbnMuYWRvYmUuY29tL3RpZmYvMS4wLyI+CiAgICAgICAgIDxleGlmOlBpeGVsWURpbWVuc2lvbj43Njg8L2V4aWY6UGl4ZWxZRGltZW5zaW9uPgogICAgICAgICA8ZXhpZjpQaXhlbFhEaW1lbnNpb24+MTM2NjwvZXhpZjpQaXhlbFhEaW1lbnNpb24+CiAgICAgICAgIDx0aWZmOk9yaWVudGF0aW9uPjE8L3RpZmY6T3JpZW50YXRpb24+CiAgICAgIDwvcmRmOkRlc2NyaXB0aW9uPgogICA8L3JkZjpSREY+CjwveDp4bXBtZXRhPgrk9+ZCAABAAElEQVR4Ae2dB3hURdfH/5veCCS00CEQIKH3DkoHKUpTFPEVUUTR71WxKyr2+qLYCyqiIEqXDgpI7xBaaIFQQksnfbPzzbm7d9kku5sNpNzdPfM8ye6dOzN35jd377lz5swZnZABHJgAE2ACTIAJMIEyIeBRJlfhizABJsAEmAATYAIKARa8fCMwASbABJgAEyhDAix4yxA2X4oJMAEmwASYAAtevgeYABNgAkyACZQhARa8ZQibL8UEmAATYAJMgAUv3wNMgAkwASbABMqQAAveMoTNl2ICTIAJMAEmwIKX7wEmwASYABNgAmVIgAVvGcLmSzEBJsAEmAATYMHL9wATYAJMgAkwgTIkwIK3DGHzpZgAE2ACTIAJsODle4AJMAEmwASYQBkSYMFbhrD5UkyACTABJsAEWPDyPcAEmAATYAJMoAwJsOAtQ9h8KSbABJgAE2ACXuWHIBlxe7Zjx+YTiNcJ+NVtjwZRbdGvsZ+NKgnkZh7Chm/+xlEPHXRevvBscgce61PbRnptRwucxKYZK3DA9OoT3HUCxrcPgq03IYEz2PnTOhxIzUQWBPLq9MDY3s0RVtFb2w3l2t0UAYHT2Pr1ahzI0UMv+zuo3Rjc2zkMfp7WixO4iHN7Dpp/T6gShS5dOqFDgwrWM3CsUxOg/j646G/sPZeENHl/BDa/A52i6qF5mK1Heg6uX96PjfO24ZROB/gEIShqICb0rOnUHJy28qK8Qso2seClAaI65F0j/yrd84GYujbbdm0M6SJt2/OirSk9PPxF5MwLttNr+kyuEKffFl3UtsjPlj+ni6w8O5WO+0rcG+Yr5E9G4aWbslwcipflcHBNAmf+JwZ7GPuafh9NZ5wUCVl2mho/L9/vyeeO18SPO6/bycCnnJqA7O8XetQTPqbnQf1pm8Tvh/S2m5RzUZxaNEk0U58fgfXEbd/H207PZ0qVgK3Xo1J/kciKOY6jB/7GZXklHaqidaN6aNZc3ka2Qk4OUnaswl7lvA4+uu64Z6iTvq3l6XFt4bvYZmqrB9pjUI8AeNka7sp0hl2bsDMzV3kSe6Al7u0TgUqVy637bPUSx5cQgYTlP+EfU1nU3707VYWvnZ+H4dA+nD293/R7qo6ubaLQsHFgCdWGi9EagdQtG7An/ixyZMV0aILubcJQs44NdYhMI1LScHXfBhxWGuKNgIodcUf/MK01y23qU05P7nRcOB+Hk0dyFdCiYjd0aBqB2+3cB/qcy9iz9YCpY/wg6vXGbfXs9FNKCk4nnUBqTAKOp5zA1StV0WLsGPSsLMeM5RwMedewZc11cy0Mzf6D8Q0A2z+bVOzfFY3UDIOSx9u7Nzo1CoI1LbM+JR6no6Ox//h5XE5Plz/KIPgF10DTrm3ROqKaPOKgfQIp2LHhAPTG7oaIGIORTXwQYPPWTcex6BM4fYxeYwEPXTM0rl8b9Spaa6mAPi0W5zdtxY5TSbii84Snd23UiGyH23vVQiVrWThOYwRScfjgMVy7YKyWqDsUg5tWQrNgW9UUyLgej0O7Y5QEOl1N+Nbthm51bKW3FZ+Mw3NWImnYWHS3eS1beTnekkD5CN68OCQkXMbFeFNVmtRB3bDqsC1H9chNO4GtG03pPfwh2jeBlFVWg+HSERw6cB67YpbjxJpYLD+7DEcPDcW7g0ahe2VPm/OoVgsrhUiReRyHj1gU3LMdoiwOC33NO42du08h1fieguwuTVDXzw/5Z8PlXGDKNcTs+BvLfpuH2Qs34WhaqhS8wfCv1hWjnp2A++/uj9vqVET5dHqhVnGELQL6E4g5CeSZzosuLdHMy0v2pY0gf0+HDp/B8WPG83n1ayIstDJCCiWXdhLZZ3F46xJs+Og9fLPhCiiLh64z2ox7FHk178CwiCqwM7AuVCJHlAMB+Tw4dyEVSTTcpdA+Eo39A630t/E0kIG0xJPYvdV4LPwrwrdZBOqqpx36TMHZmPX49f3fEdZvLLpKwWtHQedQie6cqHyewaf+xclDu7Ezi9B7oHJ4HVStUdl2P+RlIf3gYiwxvtDDs0Id9BzRC7Ze2NK2fI5ntwegXcwG/LT8oKJ+Q5+RGFzXQwM3ix45Bxbg9/Nqc33Qqmsj9cD655HlWLM/WxpVUfBG1MgeaBISnE+AZl3aiyPr12L2gp04kOmJiNtvQ4Pr5+Xo9wBOXlmFX54/iF3Rb+DbTx9E90q2x9bWK8CxZUogehGW7JfTC8pFfRDVLhzePnZ+qvL3tOVQ3I3fU+eWiGpSHwXNqvKyzyF64yzM/HINzlTsjIghuahy9gh2RG/Hnl/2YszhF7Bq4xvoz2qRMu3uYl9MPg+ov88rb2ZeqNuiPoKCfG0Xk5GIhOg1WJ1sTOLboBG6D+mCWrZzFDiTgjPHv8bUYS9gQeVZOCMNc1joFkBU3MNSnUG2UfiVX/8jpvUzGQnpmoqhby8TezNsJJbR+utxYtNkLyHbJv+8RFDkFPH1ZdvpzWdyfxMTlDw+IurbM/aNl8yZSvmLPlMcfumG0YwXRohPL9m7ZrY49X5XUcvXmMcTA8WbB9LEJUs7Cn2C2DLzPTFj2sfi2/Unxbl0Y3mZl3aIlR/cIx5sFSrkY1voanUX9/x4WrBJlj3e5X/u3Pt1hK/JsMoLQ5X+tv3zyBXnfhgvetW+8Xsa9s5fhX9PhjRxZc+f4uMpH4ifNp8Q56mZuVnizJrvxJNNvI2/La8gMXSxofwBcA3sErgws6u4vb6xvz10PcRTq2PzPw/y5TaI7HM7xPxxpvsDwaLh0LfF7Kv5Etk5uCxiY94TIxsb8+O5/XbS8ilHCZTDi0s6TsacQZxUpVEQYa3QvFF9NPI3Hhf+n46clANYvlBvPOURjApdB2FwtcIpC8Xs34ndMtILXTFCLjuyZ7xUKG8pRRjyEhC940bh+i5DMFy+QdoM+oNYs3YfErKNKfJ6Dke/ej6QGvMbITUa8U1Hosu9j+Hh3g1RO8B4yq96Rwyc8hJe/+BR9KSo+Is4tW2PXMjEQbsEUnFw9zkYjMNd6DsMQt+63rD588iTUzBbD+GsadpG1G+PlpERhX9PmWnw1AuETXkWD3RrZBztyCV59W6/G2+/fafUo8gg9LiUmKRdNFwzSSANR/bvR7JJ+2eI6oWe9YPyPw8sOYlLSLwSjb//MkaKgPqo17o7elexTGTr+xXEHPgGrz32OpYdNxrBThjVylZiji8GgbIXvJmbsXnbBeyKNdUywji/W1AtZm6DVJNYqpk9AoPRqk8Xm2pmcz5p73fszxk4KCM8PTujY217xks3cpXuNwPEtUWYv97iKj3a2pnblumk2vGGmhmoPLgHInx88qmZEdILI/s2Qscm+Wd9lav4hyOwflfcHimPDGnIvngZJpsMi0rwV80QuL4EixcApul8oGtrhMv5XZvBpGY2qh3l8sw2kWjaoF4hNTMCaiC04yjc26RASR7yERAahoY0g1y/B8a0DC2QgA81ReD6SqxYqcepTFOtWkeiQUBQ/ueBRYXF5Zh8ambPOmGI7NzGATXzFZzY9h3efXYZPLqOQ1NZpp/HY7i3g0Xh/PWmCZS94N23G9uvXjCZtevQrFkT1Ktf1WYD8lJTESfnpUx2I9D5V0Zkg8JmIwULEOIo1vxpjM1+sB/6SuvNcg9yRKHbtBILzRXxxt2D7L9BXtq4CHszSRNIwQtdGtaElzI8McYU/T8Qft5hCKtPKb3h5V/QKKvoEjhFGRLYtAbzzLeqN+4a0AF+trxmyGol7tuFQ1evSScbFHSIqF4NoaF25vuUdBb/9Jm4fuwwjldpi8r3v4Wp7SzO8VftEdi+CSuz9UhVauaF3t1bIriSlRduU80z4uJwdvsiqOOcwIpVUK+WzWGOMZchHVdjF+CT2+Yit/0HeL2tdNYhz2RO6IM+pnL549YIlLngvXImFknJGUqtPdAJbZo3Qnhd241IT02Q631VwSNVrNVGYVBn2+nVM7oTizHnFB3Jh9eInsUUVmopJfxpkKPwQzeGuwF4FCNus3MNkYHoA0dxPdvYfj88hOG3+cDfzgDIamlS4OfKIZSoVhe1buuKblYTcWT5ExA4f3gvcvKMNQmQ/T2sjw5+Nvs7G6dPnkLyNWN6T9mz7Vo1RuM6jrUkLzcNly4ewqK1mZjw7LfY+VpHxzJyqnIiIP1VxRxBeobxeeCDu9CncyWEBNmqjh5X5PTS8aNG/YkONdFILsPsau9dX5+OlH/m4NUWXyP+h/WY80Y7xP6+Ql5Ah1rtG9m6EMcXk4DNn3Qxy3EoObnB2775IC6cMyY31KiHWlWrIsxW7uyLiN/3Az5caUrgHQrDyAHoZyu9ZfzBrdgljwPxJEb11hnnsCzPl8P3vOyD+Os302StvH5Gl7Zoa68ex/+Hj34CEkxpssbfgaG+vsVri5zjSU8+hqNyCV/lqEgM7EY6Zw5aJCDEEaxYcMS8fjejQyu0lu79bC7vOTsPv6+MQbRx+IO8jm3QPiJCqo1tBQP0eTnIzsxCRsI1aQX/G/44HIERX2zF5Bq28nC8VggIcQzrV25DkkkDliO1hY0D/OUzzkZI2CGXEK3CN6ZlmEW+eJPQ3TgHzw//Epe+XoPF46ojL2MrDsoHqRf6YvJgvklskC52dJkKXt2FbdgSHY9Y0xu9T5cWaNk4HBVtVDv3WjyOrJ4H1W2GZ0gt3D+wjY3UltG5WDt3jRKRPnE47qR5rHIPUs0c8xd+V3U+9Ab5wADYfofMxemF87CJqq4Y2nhhyNDu8C/ucDdmK84t/xafG3pj1P3P4jF7b7vlzsi9K6A7vRwLdqjrd3UIu68vIm3eu3rEb9qE3ecumuaDvdCsXUs0irD+cDTkXpHr5g/ioFQrr/tzMf7+bgMOeoag5yOzcW9gtjRZ9ZV3JActE9CdXYcVu/Kgut4JGdIdzSpVtPEiLpBy7BgO7N5onqYLrh+OHrZevLOv4drmBXjFQuhCTmAYDi9SNIf6tqNwt4OaFC0z1ErdylTwSr0YjqclKA8KnTSP6tkiEvUb+ltnIa4i9uQC/PCjukrcB6GVhqOvA2pm6P/EPGUi1age8ZSbKpR7kGaquYd3mlxekqFXD0yw8waZmz4Pn718CFkmLbsf7sfgXj521I5WWpgXj52bN2Lez5fQa8Ab+L8JPNq1Qkk7UUf2YBv9IuWErae0xB8/MBxe5vne/NXUZ63H/NmbEB1njCe1ozJtY+3hqL+KCxs+x5RJc7Ar46pUTV9X1oSLvCRs/GoMBsR+gvWLJ6GjrwZ+J/mbyUeWBI4dxL5c46jFA61wV/dGCA6x/ggX+kPYJu1JVv5tLEC+xqF+zR7oZO3FOzseZ9e9h/sf3IhQ00hXySX9J5xYMlPRHKKTfKmzrAt/vyUCZToUPLhtMy6eNZrjSZGIsGqhqGxjfiL1eAxWv/UulqvN0/khS85fkXWdMZgkknpo+bl8LmbJYxJuEwfWsPnwssxS2t9FXjbWL1lvuoxOji/kMiprD0lKIW/4LU+Px5cWTcxq3hSR0rrVaFdlccJmxQVSpW/rlcv2YEXUeEx6ZxzP7dpkpYUTAluWzYe0m1GCL1pII0Jh3VGBvJcOzngfv+4+aZ6GyIloJL1VhcLqyjSvqqjTbzr+jDmAFYs/xVujW6O3HN8axWwm0je9g6k/n9cCBK6DTQICO9b+guQ0Rf0lVb+N0bC2LwKtGlrmIW7FCiyau8D8oi+8KsEvvL6Ftz/TM0Qv3YZu/VgRurp3VyjqZbUKeXkxWD8/Wx7qMOwuR0Y8ak7+LJKAowt+bzWdQWwWXw9uJqT9MvW4QPvHxKdrzlktNjdut1g8OcSYzpReVyFc9P/Z5GkiT7oTOLREnDhlNbvYdK/pGm2/FUetJynjWLmIPXOOeERtu046LJi40XodDDnizCdtRCUfj3ztr/DmHnE1w+Tc4NgKcS4mWWTb2cxJHFssPn9ohBj4xmIx166DDuvV4NiyJWAQC8Xz6v1Bnw+sEuk5VpxZGHJF3Nd9Rf8mqkMZ470e9PRfYvYek+eUq0dF4tHjIiHJRhtyUkXO9l/FE+brBYkKw2aLQzaSc3T5EzCI1eLNml5Cylnjc2Ho12LXGWu7TxlE8pYfxLTBAfmeHx6N+4tHF18zNiTrmsiLXiFOyWfI5b+fET2qthLDfyn4kDCInOuzxUR5vQA8IX4vfwQuVYMyG/HqLpzBmdRkpJheBRq3aYEGEXJxbcFw7QgO/joVDy8LwZjhg01nPRBQqRuG9KH3eQOyru3BV499j0VWtCwCR3ForzFbwP2DLUbIBS9Ulsd58Dx6GNILoBJ0XoEYMqpn4QoIaX3410No9koMxt43FjraN1MGsv6e2D8C/n46CHEcc1+Yhd/PXsNVG5pBcfVf/DF7JTb4PIAnxw/HPVaHQYUvzzHlR0B3/CCiLS4/aHhfeHkV6GBpnY7V/4e+03ehUuQgqTEyekEgtePdPZuiYQR5TrmGA6tWYs7agzhu69ftXQHeHe/EuztelQptCtkI3H/StMRPieB/GiOgOxODo3qdadkY0K1PV4SEFjSrkrL22CLM/m4GVie2RNcOqj2ML+rUaY/uncktbxauntiGb56Zid8Ovo/hA+YCbyzA3JHByMzMvPGXmojcRb/jezm2zhjbH0OVc8bd0TSGximrY+unWeKNSdy8GTsvXlC2sfKQ4rB6lVBUrGRxGYMe6ZcOYeWPj+OhGQZ0HvsaHqr7rzGBLgC6tgMwqJY8zEpC9vo5WNLpBTxb1yK/6avu+Hz8cowOdOjbjDJoIOTl4tTSr7DTVBUvfUc0amBZL7mxfa6cT1n1CAYMm4P0+xbi2cj98NPRS6t81YgYiiERcisveaxb+xWWhU/AHY3DUMuKmklc24IFM37F/KTBmPDcMAyqrxTB/zRO4OLCGVhv+jV6oB3C6xvk5gVqpeX9oZdLh9Y9jZH3zMLxvrPwcIcAtAg2riMy1O2H25sEI5KWZx7fjhNXvFA1shM6B6v5rXzq/OHRaCBGmab9haeHnJrhoFUCl1cvw5Z0vTLcpRetOrV84GOxXNsgrdWvHl2Ez957DZ8evQ0j+vXH4OpHjM3xqo+wqM7oTi/gCeeQLLcYXd/0EQzeMwPbcy/i38caISAgIP+fXO8beD9N9MmXvblDlXNVAp7BH1oF5GT1KhPBK3BWLiPaiwtxRjoGaWe3Y+9+HDl4SXnDyrlwADtnPYdXH5TbW72ehIoTXsKMqR3h4WF6FAghXehlI/16IhJ3rcBbS+ri0Q+M7+oFedMDbJuMDMAU3Nev4NnyODZIoXoIK34zeSiXVcjVbcTnfx4zv13mHfwDnz/UDpFDZmNNV2nM8EU/BFWQb7Pqg1fkIDNNep2KWYE3vvTHoGk9EVav4Nuu9Ip19QjWym271vgMYqFbHl19k9ckLc2Sn5PNy4gM2INvlhxEUkq6co/kHVuBX57pjxZ3fI2FTd7Ehk/vQIsoOWmj3h/ydTb7+nVkXIzG6mUncK52C7Tpa0WblK9+comdZwPUI6MJKYQz2jeVs8octEhASCev/yzfgATT+l2DXOexcP1BXDyXZLw/Tv6NxW/cjYn3Por/29AMo6c+jLF3NpEaM/XxnoccfRYyky7g1OZNmHO0Bka/WRNbN2QiMDDQ6l+Qn5rXE75BQUqajMmjMEaLgJyxTmWiOD8/R7zQq7Go7qkM4fLNPUhmpmOd0FVqIlq88p1QZj9TT4ujn/UrlNarQSfx9L/Wa20Qx8Q3TUzl2ZpDtZ619GLz0oV+74uiI3TC39tO+2ne9/Yp4qfcXKHM7P09SVQrmN7DVwz7LVGk5BSsbp4wnJktfvvfI2KQnNNdeabgeT7WNIGY10UXeX9UKNjf5t+GvKd1XkLXfZL4MuW6UKb2d38k7mkfXOD34SmaTf7ewf43iIyEDeL9BnLzDEv7CU2DctPKxX4m7q0ZKkK87Dw/5OYxaNhbjFu4QT4FZYhdKb5/pEWB+wMitNs48eHuojjmmp5ZHkLXe5ZG7GSKqrNznZdzhqUfkv+cLHoPniaWfveY6NOuUqGbgYRvxVaTxAMf7RM3ZEayiNv7vpBvWOb0usB6otcPF21U2CAF1hLxpCn9wOU2kpVxtCH9mjj1boTw7PSptHcaYW7LjRcOY/tajF8ndubeMKYxiBXiRdkWOagx5/F8dZe4kn4jjbkp8fPEyz2GiSET/hBLbRicmdPyF80RuPKR/E00+1wcW3qfzZezpiN/F5vSTC9lsgUGsVV8O7iFkNpD8/3hPeQ18eMuawY31pqcI1Kv/KDs3hVUc6z4MM5aGo7TAoGEH/qL2l3fF7vmPyjqVfU097flM6TBwC/Ee6vOikRThQ3ipNj46Xj5Qnfj/iDBPPFPB7YlkjuonX67snzZk4OByTaMQLUAxonrUOqC1yBixconO4lGoz4XO2NTxdVd74tH7/cW1aobb4iwKh3ECzPmimMpyYUx5lwUF9Y8Ih5oCeETPEo8vEnZzKxwOoqR1sBi+UjlppSuGMVs66nKOJZGFf+KmW1kW+kGlnU8vnSEaNfxxo+hS5tJYkHsaev1OvM/8WwfCD+0FT1+2yeSrFm5moTuE4tOiH9TChdDP8CTl5eJ9xfuKXySY8qdgEGcEN9Hyfth/HrFivnC3xNFX9nn6kO1Y6sHxY979otsg/UXrq8eqSQ1SVGi/afrxZLYNIfbQy+EB6ZVFPZfZh0ujhOWEgGDOCX+GC5Hs2Pni3ip6orf9JS4ayiEt7fxHolsdKeYuWaTfDYUUoMJkbpd/PPZ7cqWfoGtJ4vXdzuyl6rchjV7n/i8qXzp9w4S96wppYa5ebGlLnjFua/Ey71qi/Anlono+NLbCZZuFuUBRm94cvRwWAsda0gXadufF93hLZp8buel4SbrqrzEjLtNTF4j91e18rtLStsh5s18UDz98NPix/ibvAhnK10CsW/L+0O+XH10TmRa7rF8i1e9sGqOmNIqWGpMwkTl8PvFtF/2injTLZgrp3H2/DZMwLuqCHhu6y1eibOXKgH58n1/mLcIsaXtKvGLy2VEWXPFo/KeDPZ4hpcRlThfY4GlLnhJTdKvEUTnTw6KE1ZGZCXRLkPuAbF2bGPzKIFGvM/bGESWxPUcLcM8qiiFN0dS3xNXdWRk87P1JNFPqvA5aJOAomaWDzmaGsm2Mqi9uVoniehfnxejK9q6P3ykSnuUmPqtrWmbm7sq5yp5Ale/aCsaBOrE7bMT5ai25MsvVCJpDv+QL2WsZi6EpiQjVNM1+dwu+SCwDl+/shHRJ6MQ0cBf+hkuyWsI5GbPw2S51tXDuxX6zT1uLjwDX+P9cB0CdZPxi4wl6VT2IRfX05fg0+kp8M7rgcjGJVeDxFkDMPqFr7D2ZNFlhkv/vT16tC46IacocwICS/HW1GS5TrszWsllPZ5mK+VbrUolNL/jYTz+xovoVLXajcKkftLjznF4eeE2HMz5Ax8+bN2v840M/K08CQisxCeP70V8ehtERnjC24rfgpKun9DrsXbhUmnp7oUmzRqWdPFcnolAqXZl0q9fYE5qjnRr1xD16vogwMq605vvCbkcwvduzMwYjk9sFuIFP3muxJ5nNq9T+ITITMPZ797Cj9LJY5CuMSLqFU5zszGhDyzFX/fKZUoOvFHovHy0sSXizTbWhfMlfPksZsr2+cmFPE0bkKOUEgwVG6LnlOnYNGmavE9u3Cg6Ty/pmEPuy1yCl+KiSodA4g/v4lu5olLkSeco4VLwlsGDTOftj74/ZyDjB/nc9CnRkVLpQHLSUkvt9yewET9NX4vT6fSj9yrBt3lL0jq5sbu/Bh8iuci4vhxfvxwrR9vecqGIbL9ltW/1u6cvfEq0wFutEOcvHgEh74tV+Ojx44o2RifvjtLoThKyPvKPg/MRIG3hV5P/RaLcE8FH3h03nKmUfltI+PqX6CCp9OvsbFcotV9l0q8z8P2FDOmMToY64Wjo5yedWrhHoNFu7Hev4Uulub643qUJmrlH07mVjhCQXoYSvvkvPjClzWgaCZoMKIMBjSO14zQaIJD4w3RIB37Ki1l2wwg085QjXg3Ui6tQMgRKVLulVin/aFfG0jys/HOPB4vlaJfaLv/YHZ96a/CnfJTm6pebR7sKEPlQLY0RL8N2TgKWo12lBXJP5pKb/3dOJq5W61IRvLrNy/BLYqZxtEvEmtZBhK+fVJm4QZA+lw3rFphGu7K9nv4wRIZrZLMGN+Cv9SbKjQ68Vs0zj3aV6rZujCit15vrV2YEdP/8Kef+5YYo6hWbN0RT6T7XPQYuaqNd+7NUVM0pp2OQrO7gLvk1v70LQiqRB3fXD0Kfi/Mndpl/NB7BlTB08G2u33BuoWMEDAZciNlqvj8oU487NeFU3LH6c6pSJ5B84gDSDGaxi06DesoVIaxoLnXwZXiBUhnxBt89Aa/20ClzuuGDv8Y3QxuhUUgZtqocL6XzD0Tt/zyLV+tLLbNnCPqPnYHZg/hdtRy7RFuX9vRGtYdexYcRxmpJV5BYOlxbVeTalC+Big/8Hz5sZ7Rybzz8Z8wZWgUhbqEuLF/uZXl1HS0KLvkL6pGTnIiUbAEPv0oICfYtU6u8km9PcUvMRmZCMlLzPOATINsfxG+rxSXo2ulzkJWQhFS9fLj6h6JKMN8frt3fxW1dLrIT5fNTbs/t4R8i7w+WusUlqPX0pSR4td5srh8TYAJMgAkwgfIhUCqq5vJpCl+VCTABJsAEmID2CbDg1X4fcQ2ZABNgAkzAhQiw4HWhzuSmMAEmwASYgPYJsODVfh9xDZkAE2ACTMCFCLDgdaHO5KYwASbABJiA9gmw4NV+H3ENmQATYAJMwIUIlIrnqvLkM3z4DW8ES5YsKc+qFPva48aNQ1pampLvjz/+gI8Pr98rNkQ3yzB9+pvYs2e30uoJEybA8v53MxTcXCsE6Bk4a9Ys5Uy7du0xbdqrVlJxVFkTcDnBu3Sp3MTZScPixYuRnp6u1D4vT+4HxoEJFEGAhK56z/ft27eI1Hza3QjExcWZ7w93a7uW28uqZi33DteNCTABJsAEXI4AC16X61JuEBNgAkyACWiZAAteLfcO140JMAEmwARcjgALXpfrUm4QE2ACTIAJaJkAC14t9w7XjQkwASbABFyOAAtel+tSbhATYAJMgAlomQALXi33DteNCTABJsAEXI4AC16X61JuEBNgAkyACWiZAAteLfcO140JMAEmwARcjgALXpfrUm4QE2ACTIAJaJkAC14t9w7XjQkwASbABFyOAAtel+tSbhATYAJMgAlomUCxN0m4cvmyltuTr27OVFequEEIc/3j4+MRFBhoPuYvTMAagczMLHN0cnIKnO2eN1eev5QKAbon1ED3Ct8fKo2S+QwJDYW3t3exC9MJGYqTS6fTFSc5p2UCTIAJMAEm4JIEFi5ciLvuuqvYbWNVc7GRcQYmwASYABNgAjdPoNiq5kCNqz/V/WwJidbrWrDbnLnuBdvCx2VDwPKe8fL0hK+fX9lcmK/iFASys7Kgt9jb29meiVqH7OPjc1NVLLaq+aauUoaZLFXhxdSil2EtrV8qKCgI6oM0IyMD/v7+1hNyLBMwERg+fLh5o/PPPvsMTzzxBLNhAmYCM2fOxJNPPqkcDxs2DEuWLDGf4y/lR4BVzeXHnq/MBJgAE2ACbkiABa8bdjo3mQkwASbABMqPAAve8mPPV2YCTIAJMAE3JMCC1w07nZvMBJgAE2AC5UeABW/5secrMwEmwASYgBsSYMHrhp3OTWYCTIAJMIHyI8CCt/zY85WZABNgAkzADQmw4HXDTucmMwEmwASYQPkRYMFbfuz5ykyACTABJuCGBFjwumGnc5OZABNgAkyg/Aiw4C0/9nxlJsAEmAATcEMC7KtZQ52emZlprg37aTaj4C92COTk5CDP5ASfHLZ7yo0SODABlQDdG3SPUKB742ad+qvl8WfJEGDBWzIcuRQmwASYABNgAg4RYFWzQ5g4ERNgAkyACTCBkiFQ7P14S+aypVfK5UuXSq9wLpkJMAEmwASYwC0ScDlV8y3y4OxMgAkwASbABEqVAKuaSxVv8Qrv3KULGjdurPxlZWUVLzOndksCkydPNt8zs2fPdksG3GjbBOieUJ8pdK9w0AYBl1M1awPrzdXiUHQ00tPTlcxCiJsrhHO5FYGLFy/ixIkTSptTUlLcqu3c2KIJ0D2h3h+RkZFFZ+AUZUKAR7xlgpkvwgSYABNgAkzASMCtR7y0vs1gMNi8F3Q6HXx9fW2e5xNMgAkwASbABIpLwO1GvKTKfeKJJ5SF5CRUyVGFrT8/Pz+0a9++uEw5PRMocwIdOnTAnXfeWebX5QsyASZQfAIuN+IdPny4mcKSJUvM3+lLekYGunfvjpjjx0HpAgMDlfP79+9HUFAQGjVqlC+9t7c3evfunS+OD5iAFgmEhYWhTp06Wqwa14kJMIECBFxO8C5durRAE28cTp78KIYOHYqdr74KEqpquPfee/H000+jPY9uVST8yQSYABNgAqVEwOXW8dK8rBosLYMXLVqEbdu24YMPPlBPK580zxsYEICU1FQEyE97gUbGu3fvken84eHhgdzcXGRlZcuRckPcfvvt+bKeOnUKa9euk2psP0WtTcuDRo4cieDg4HzpLA8OHDiA06dP459//sGZM2dQoUIF5TohISHo0aMHRo8ebZmcvzMBxWI1LS1NuVciIiKYCBPIR+DK5cs4f+GCEkfPE75H8uEpvwMpnFwqSJK0Dkf5s2xYTEyM5aH5+7r160WzZs3Mx/a+SK9YYsuWLaJPnz5K+ffdd5/YtGmTiIuLK5QtISFBdOzYUUk3ZswYIdXeIlevL5ROjZCCWTz/wgvitttuEytXrhRJSUnqKXH+/HlBZfTq1UvEnjljjucvTIAJMAEm4HwE3GbEa+vV5qmnnkKGnPv95ptvbCUpFN+1a1dl9Hzy5Ek0bNiw0HmK+PHHH/HPhn/w0Qcfolr16lbTqJG7d+/GfePGoX+/fvjfjBnwsrLDjLy1lPlpWpe3b9++fKpytRz+ZAJMgAkwAe0TcDur5oJdMmfOHLRr57jl8vXr1xWhGxoaalXoJiYm4uGHH0blypUx++fZRQrdrVu3gixSJz/6KGbOnGlV6FKdSYX+zjvv4PDhw5ghhTMHJsAEmAATcE4Cbi14ac722rVraNmyhcO9t3PnTiXtXXfdVSjP+r//xtSpU/HWm29i2LBhhc4XjJDqZIwYMUKxnP7vf/9b8HSh46ioKCWO5qs5MAEmwASYgHMScDmr5k8//dThnpBzqUpaOcfrcJ5/N29W0loaU5GB1utvvIF6deth1qxZDpdFI+PL0vhh3bp1DuWpUqWKkm779u0OpedETIAJMAEmoD0CLjfHWxzErVu3RppUHZ+Sc7WOBnV+l6yWw8PDES39K48dO1ZZivTTTz85WowibPvJOV1awrRr1y6H8l29ehXVqlVT0tKcLwcmwASYABNwPgIuN+J1tAvOnTsHWr7zn//8x9EsUOd3aeTZoEEDZU728pUrICFMc6/Tpk1ThLEjBdLcMgVpGW1OTvXJy8tTjtu2bWuOV7/QeQq1a9dWo/jTzQmQA3xeTuTmN4Gd5vNyIjtwyvGU287xrlmzVsHerl07h/Gr87s01zphwgS0adNGmc8loycKb7/9tsNlrV+/XklLo+4cU65u3bpJQ692yl9mZmahstasWaPEkcMPDkyACJBNAd0zzzzzDANhAoUI/D5/vvmZQvcKB20QcFvBu2OHcZ5Uro11uCfU+d0aNWqA5pLJ/SSFSZMmKQ4MaH5Xrhd2qDy5NldJV6tWLcQ7kIOWPKnWzA8++KADOTgJE2ACTIAJaJGA2wred999V1ERt2jhuEXz6lWrlD6kEa6lByryePW+ySPW9OnTHepndW9M8mhVz4Ec33//veIp67PPPkPTpk0dyMFJmAATYAJMQIsEXE7w7t27F+qfPeC0zpaMoxwNlvO71vI9JFXPZPj022+/KQZXRZVLamUK5ISjqHBcbupAy41oYwfaWYkDE2ACTIAJOC8BlxO86hxpceZuHek+dX7X1tZrPj4+eP/995Wi3pBLi4oKTz75pJJk7ty5dpOS0B0yZAg6dupUrKVKdgvlk0yACTABJlBuBFxO8JYWyWXLlilF02YFtgIZPZGHqQULFuBv6UzDXiAVN80T//HHH/j111+tJl28eDFatWqFyZMnY+uWLSBvWRyYABNgAkzAuQm47XIiR7vt448/RlJyMsjLFC092iNV2WfPxmHSIw/ncwdJuwp9+eWXuOeee5TdiMhXM7mDfOmll5Qdhqxdj0a95Ijjq6++Ai1vqlmzprJkKVPO+7788sugZUu0XISXD1mjx3FEgO4Z2nGGDP44MIGCBCpWrGjekYjuFQ7aIOByDjRsbQvoKG4SsrnZ2agshZ6np6ej2WymI5eUqscpm4n4BBNgAkyACbgNAVY1m7qaBCQtNr97zN1oI51XHD169JZvAirz3nvvU8q9Ih1tcGACTIAJMAEm4PYjXhKOBuktqnOXLoiNjVXuiD179sCa56ibuV1ImFcPC4O/XHJ0Rqqj5SSw2e3jzZTHeZgAE2ACTMC5CbjcHG9gYKBDPULrZ8nfcRcpcC2X9JB1ckmomM2VkIKW6pSenq4IYPpOPpcp+Pv7m5PxFybABJgAE3APAi434i2q21RXjC1btswncNV8JTnaVcuka5KTjYKBvFFRYAFckAwfMwEmwARcl4DLjXhtdZUqcKtWraqMPq2lK/HRrsVF1FGvRZRZGLMAtqTC312ZAPkl93HlBnLbmIADBFx+xOuIwFU5/fvvv4pDcfW4JD9pB5nq1avbLZL25q1QoYKShkfBdlHxSRMB2guadrTy8vKCt7e35rkYZA3ZorPsuonuDbpHKNAUGg0uOJQ/AZcWvLZUvOWPvega0CiYhW/RnNw9BbkRXbp0KYYOHap8FuSRkZWDxMQEZGdlQBjs7+Gs03mgRtWKCAgmRy26gkXxsRMSmDlzJlQvecOGDcOSJUucsBWuV2WXVjVbm1d1vS7UZov0ej1Wr16NY8eOISUlxaFK0mj/scceU4zRHMrAiWwSIBkbFx+PHbv2IDcjFYbcXAgpTPP0eXKErJejHy/5l3/sqfPQoUvLBgiPagNP7yCbZfMJJsAEbo2ASwteslqmEBQUZHNe99bwcW5rBGKkf+lBAweal2dZS2MrrkmTJqA3cw63RiA+IRmbtu9EsC4XzSMjUbladeTBE6dPn8Gl+JNo1KABqlavizyRBw850qVlbt7SX0yo3DzE05ut7W+NPudmAvYJuLTgVZtOOwtRKEoAl4ZFM13XEZU3vSQUVT8qS+shLi4OraV/adI2TJkyBfXq1TO7zNywYQNSU1OtClYPDw8lLW0IweHWCOTkGXD0zBkEGtLQqWtP6dq0ljK/p5fvoVel2tlbVxVRjRrAt5J9N5N6gwHZ0iLfz9dXEcxUK9Jk0LxhQICfPMo/Ys6WHt/Ic5yHyeObMOTJeeei5xTp9Tg5JVVeS6rDTS/LnnL07evjh4ohwYWuIyM4MAGnJuBygteey8iiBDDtaFRawtfWXaI+aGydd6Z4eiiPGjVKURe/+eabZqtttQ20w9Po0aNx//33q1H8WQoEcrKzkHAhBm1bRKFGzbrmK6Tn5CEpQ7pDDawA3woVzfG2vlyVL0kxBw8gyD8QXt5ecj9oPahsHymI27esD51v1XxZt+/dA528B/x9/ZAtVdpBUl5HNW8u0xsNBvMlNh1cSUzElYREnIg5jmAfKci9fKRKXCA7W49MOS/dtlkT1KhdSzqgKbq+1srnOCagRQIuJ3gdgawK4MaNGyubEDiS52bTqJ6rLPPT0iK1Dpbxzv79s88+U6zCaWOJgoFGQ7QT0wsvvFDwVIkcJ0sf27ShhJ+fn/JHLwF0zVw5t9m+fXtlJKZeKCYmRpl6IOM1sgSmERw5VPGVAqVp06ZqMuWT+unIkSPwl+X6yD+9LI/KbN26db50WjoI8PNFz87dUKN67XzVunLpIi7GnUZwuBTGnjRitR8qySmapo2bYO+Bg0iRAtLPOwuRUW1RtXJ16LxpJJo/XErPRO6Vy6hWyRcNIloiMMAHPt7Wr5OpN2DP/sM4d/IIGtSpjE6tohBWoyZ0ntIyW46as3P0OHshHrt270Dl08fQTvIOCQvPf0E+YgJOSsAtBa/aVwcPHlRUW5bONMiTFY3MaDu+kg6WXqusla16tKJzzmjRTIJr5uefW2saNm3aBINUXUZFRVk970gk7fbUU27LmCHVnwWXRdC+xbNnz8acOXPMxlw9e/ZUXgTq168PWr+thuXLlyv1US08aSnO2HvHonOnzoUELwnzd955x2wNSoJ9woQJoJeMEvVwplaumJ/0MqMuJ1Kzenh4FhK6tIwnIycbHnnp8PV2bFGPv+TiWTUMPhXOwHAtAa0aN0T9JpFSlZx/2VKO1BUfOnAI6ZfOoVeXzgirVhWBFSqr1Sn0mSpfiDZu3YY06b88olEdtG7ZCt4++T3O+fl4IbxuLSRmtsfpAztw9NhJdA1rIMtia+tCQO1EkLHixIkTlRRauF/tVNWtTrncciJ7qmZbPau6jyQ16YoVK0pM3UwbI9SXRiwe8g1eFarOKFBtcStOPC1poHXS+/btK042c1oa0dJolNY605pomg+3FqZPfxOvvTZNWTN96dIla0nMcZUqVVKE9CeffIKnnnrKHG/ty+DBg5Uyv/vuO2XNrLU0Wo67lpmDPQeiIRJj0aZ1C1Sv2cSh6l5IvY71a/8B0pMwcADNF9eT+W4Iv3PXkuTvZT8q5CUiskUb1Kxjf1SaKVXV86W1u7dcLlc1NBi9+wxQLKxtVSY1IwfLVy+Hjz4LA/r3QlBF3trOFiuOdx4C+a0jnKfeJVpTGsWQQFy0aBFo/eyHH36IAwcO3PI1qlWrhgS5CQMJXSrfXYUugfxFjkS7du1600zJUEt9ebFXSHg4jYoAR3aDqlvXOP9JQt1eoI00yAnB999/75RCl9qWeu0Kkq/Eo3JoKEIr2R6NFuSQk5oMXV6WtKOShk86GuneELrnJZedWzcjvJofevUZWKTQzZOGUztPXIROGlJVqeiLPj072xW6VBdfqZMT8pLJ6ddx+Zpjy9IKtoGPmYDWCLi1qrlgZ6jqy59//rmQKrNgWkeP3VnYqoz27t2L5KQkqfZtr0YV65NUyDRPSyNmspq2F2qYNvsmozUSqDSqtRa2bNmC6Oho5dS5c+esJTHHvfTSS6BRsbOq6shqOEuu3fXIy4W3b5A0irKuLTA32OJLruToKzU21apWQIUAaS0lg5yexa7DMbhweBfad2qDunWbSPVz0Y+SVDnvHrt3M7w89PD284CHX9EvAFT3PCns8/J0cqrihtBXKsL/mICTEuARr5WOUwWwlVMcdRMEVq5cqeRq0aJ5sXPTHOuixYvx3//+16G8NeQWjGogtbS1oJfGVK+88gruu+8+5bS6HaS1tCSgybEH2QE4a0jKyMVFOVrMys6AQdD8btFCktqamQecvZwqlxDlITy8CXz9gpCcdh2z58/DkZ0bZFyYnEqJckjoUnl/b9mJ3JxchEjjwl7SlsKRQA8oH2kb4CEtneXY15EsnIYJaJ6AywleUhWrf5qn7yYVnDdvntLSqGbNitVish5+/PEp+PrLLx3OF2YheG3N8X75xReYNGmSMoqmgskwy1ogAT1t2jQ5Z/yatdNOE5ecdBmJV87DxyMXgX6eoDWyjoSUlGTEnTslLbkzpRAOwOlL17F5wyZ4SUHs5e0rVb/XpSDNdqQoRWSmXTwLL08dPAN95GjXvt9ytdCcPKGsFpbZ8lmmq+f5kwk4IwGXE7zqXCqreLVxO549exaHDh1SDKMCrWyNaK+W06TAe/rpp5R9jO2lszwXKucw1XDx4kX1q/nzwoULiivLe+65B7Vq1VLiKZ219dSqgA4OLrx0xlygE3wxSN2wtxy91g6tgpqVq0oBJl1UORD0uVnwl3/ZOQbs3X0Ah3dtRPd2LdG0bWe57McHSXKO99o1+2p69TKp8gs9bHSGXFQNLtqpBuWj8W1c4nVkyfXDgX4+qFyx8NaalI4DE3A2Ai4neJ2tAyzr21mq32htMf2RpbUrhDVr1irN6N69e7Gas/7vv6WzhmwMlK4nixvCGzZUspCQLRiee+45fPTRR0p0jRo3PDddlRboloHyrl27FmPGjLGM1tz3yZMnK/cLjeCthVwZmZ4toJcWSgEVQ+AjnWc4EkjoJWXnSsOqPITI9bi16lRB/wF9UKlmbbRsXB9+lashT+ePuLPnpOGZcV9pe+VeS8kDvQD4+HijnizDkZAtNR7HjuyT90EmQkMqISTUsVGyI2W7Sxqyj1CfKXSvcNAGAccme7RRV5evxSFp7JOenq6009oIzBkBLFjwp1Lt9u07OFx9siJ+7913QettbyY0jojA6VOncO78+XzZ169fryzvipS+iynkU0vL+eBqFts2WgrofIVo7IBG6zQPXtDxh1pNGttWrlQBjerXU5bvePlbNzZT06ufmbkGxJ6/Aul9Eg0b1kCbtl3lWlujD2c/L09ERUYhOjUJsadPo06dOqhZqxHpgtXshT595IYMpOH2kPPLlYIcG7kmXs9EllzOFOztIZ1ryHXYnkbjrkKFc4RNArRBCd0fFNT73mZiPlFmBHjEW2ao3e9C9KOnHYootGzZwmEAjz/+OGg7s5s1ciP/0BTOW1gr03Kg6dOngyyU1ZBP8Fqs+V23bp0UNg1BGzY4e6AfeO1qoWjTshlq167jsGV2dmY6ki/FSUGZg8pVayhzupYsGtashgq16smRtD+OHzuMrExSJtsOoUFS6krhmy1Vzcdiz9hOaDpzXbq3PHnmHAyy3LCwUOl4peQd2hRZCU7ABEqJAAveUgLLxQKn5KiTAnnsouVAjoSvv/4G/fr1tzmCc6QMGoFRUK9P32k50NNPPy3dGN4YbZETDi+TQ391PpgE9FtvvVVqri2pLs4Q0uXSHz8pKwOkMVZoBbkEiXYwsgj+0ndzVHg9ePoH4MKlZFy6fF7Ok8uJZBuB/FJ5yqVd0kAZsReTpVGW7amUlPRsHDl+GpdOHkatmpUR2aw1PAp4trJxGY5mAk5BIP+vySmqzJV0FgJt27YF7UhE86XkE7moQD6RV65cobhvpB2dCv6R/2UK5LmKzpEvZmuhdm3jHCKVR+HMmTPYvn07aNP4gqGJyTfzeZNamvxMT506tdAGDwXzufJxrpyLPXspAfqsHLk5QSD85J+1UK1qNfgHBsvlRh44sG8nEhOuWktmjuvVtQv8gkOQlJSGY4f3yFFy/rlh2kM4XrqmPHDkGM4e3Y+qIUFo1bw1qlQzGsGZC+IvTMDJCbjcHK/lw1X1xevkfeTU1e/Vq5fD9aedocgKupsVD1ckdNVRab9+/RQPUqRSttbHNU1ONGg5UrpcXvbMM8/A2sYNVDFSKR8+LJ31S7U0reelOrz44osO19mVEpLP5UQ5v54gHY+cjt6LPLlUKDU5Ry4puogG9bzhExAkm2t8V9dLxxrxV64iJ+O6XBusR2KKwLHo/WgY2Uyqho0ah4JsalYKQY3mnZB0fC+ij57C9cxcNIowLjGTl0aS3GRh956dqCy1Eg3r10JLue7by8+5LcoLMuBjJkAEXE7wLl26lHvWSQnQdoG2tgwkozPVPzONXtXv1ppqOXc7U25m0KZNG0XAWkuruo2MlfOONNK1JaCt5XW5OCn9aMOIylK13L9XT+jkHslSfywFq/xTFvdYKMikzriCtw49u3YyO5GkdB521ghT7g4Na8GrUQ0kJSRASG9atMEDBTLLqiiXDPWTm2CQBTOtE+bABFyVAG+SoKGeJf/Q6oOI1LQcbhCg7fnIgxQFe5sk0Hny6Ux+sik0aNAAR48eVbb8UyIK/Hv//ffN87nvSkvq0tq2sMBlS+yQLFaJB7GJkNbcHJiAJQHalvS8aVkd3yOWZMr3u8uNeMsX561dvTS2Iry1Gmknt+pXmWpE32n7RlvBcgvAL6XXK9qu0FZQ54Np7S+ppJ0tsLB1th4r2/rSEjnLZXJle3W+mi0CLHhtkeF4TRC4++67QfvwkhtQ1eHFkCFDFOMnEr7z58+3Wk+a/yVL6qIccKhlfvvttw4ZgFm9GEcyASbABIpBgFXNxYDFSZ2HgIEc69McpQOB1PvOuvOQA83jJEyACWiMgGNPJo1VujSrQ1ayn0mDnMsWDhVK83pcdukQcFTo0tW1JnS//fY70AYNZRHIWnznzp0ldikqS132VWKFckFMwMUIuJyq+dNPP72pLiKfpuRp6XO5c82QO+64qTI4ExMoCQK0MQTtDOTn54fHHnusVF4MSDhu27ZNWQ998OBBdOzYsSSqjk2bNin7INMmJTQVQFbSHJgAE8hPwOV+FU8++WT+FhZxpArcl19+WbEOpeT3/fZbsXbEKeISfJoJFIvAJ5/8D49NflT6STYom2WQAJ44cSJKYsctsg7ft2+fInD/kc5NAqTnqQED+herfvYS9+zZU7oJXYMM6RyDnJxQnWk5l73lX/bK43NMwBUJuNwcr6OdZE3gUl5yK/jcs8+Wi+AlFWN2ttGVXmmNdBzlw+nKlwAJKnXDDKrJ9OlvolKlioUEME2NxMXFKZXt1q0bbC1DUwVuUlIStsl10GqoLLdRpPXLJRlo96eExERzkV06d0ZISAgLYDORsvuyd+9ebNmyRbkgrVm3dDBUdrXgKxUk4HaCV10rO3ToULMnJEso5LnI1sPLMl1pfLd82JIVb0mMcEqjnlxm6RMYN24cfv3110IXWrVqFWi5FO00Q/cHPUhVpzFkm/DEE0/ky0MCN0l6oroUH4+FixblO+ct1cAtW7bEqFGj8sXf6sGff/4JUl/nmlx8quWNuOsuuctQDdQIC2MVtAqllD9psxFVCzhs2DCrnt5KuQpcvBUCLqdqttJGJUoVuDTvRI7wrQUaMahOGqyd5zgmUFYE5syZg8WLF+cb9dK11eVRpLFp1qwZEqQHKGtBFbj75IjHcoRrmTY4OLjEhS6VT4Kc/GNbjnopXhX8qgAOkZsmsAqayHBwNwIuL3hJ1ULBnsBVO502EycvQGoeNb6sPsm3sBpo5B1gsZOOGs+f7kPA8n4o2Orx48cXjFKOHRG4akYysCq4Z7F67lY/7Vk2qwKYVNBtpIc2FsC3SpvzOxsBlxe87dq1c7hPbD3MHC6gBBP2kD5rOTCB4hCgEeb69euxfccOh7KlpKaCPHuVV6CROP117tQJffr04dFveXUEX7fMCbjcOl4arap/RJPmNeiPAxNwdQJH5TaIiVL4ksGUswSqK9U59vRpZ6ky15MJ3DIBlxvxWo5whdwtRd02rrOc202U82HkVN5eoC3laOP28giWdWvUqJHcfJz2bOHgrgQs7wdrDOheJUcvtOyIQvfu3fHggw9i165d2Lhxo1zOk6Us67GWl+LIcUilihVtnb6l+GS5Jl7d8MNaQbSMyd/fD7RtZIcOHawl4Tgm4LIEXE7w2uqp7dJZAIWiBPCyZcvKzapZrRvVk6xCaf0mB/ckcOXKFdSXOytlSuv2goF2XCLHFAsXLsQX0uELqZcpVDQJURJk9KcKYJorTpW2CwVDsNzRaLJ00BFYwrYEtAfyF59/rlhTW7umt7c3C9yCYErpmO4JdSMNdZ/qUroUF1sMAi63nMhylEgjXlth8ODBOHnyZKERMC3X6Nu3b6l4C7JVF45nAgUJWC4tU8+pApc2jahSpYoaXeTnJTkqJitpawK4LNbxUgVJyJPApWVSlvslF1l5TsAEXJCA2wpetS+tCeDyXMur1os/3ZdAwdHuzQrcggStCWCy5hhkNAAAFWJJREFUKH58ypQSG/UWHO2SKptU2ixwC/YGH7szAbcXvGrnqwL49KlTWL5iBY96VTD8WeYE1NGuOs9f3BFuURVWBTDNwdJcbEmOelWvVarAJQ9svCyuqB7h8+5GwG3meIvq2BVS2FKgN/ORI0cqbtZ4Y/qiqPH5kiZA/o1pj+B46WmK5vlLw3sZqXrJTSS5pPz440/g6+ur7IbkJUemtxJoRyUqy9/PH1NoFF1ORoq30gbOywTKgoDLjXgtPeGQMwEOTMCZCJAhTGkJXFscSAD/+OOPirC0lcaR+M+lQRVZVbPAdYQWp3FnAi4neN25M7ntTIAJMAEmoH0CrGrWUB+RmlENpaFiVMvmT9chQH7H1fWyPj4+bI3vOl1bIi2he0P1TU9GbnSPcCh/Ai7nuar8kd58DWjXGTJEoT9LIXzzJXJOVycwevRo8z1Tnu4fXZ2zs7aP7gn1mUL3CgdtEGDBq41+4FowASbABJiAmxBgwesmHc3NZAJMgAkwAW0QYMGrjX7gWjABJsAEmICbEHA54ypHXUa6Sf9yM5kAE2ACTEBjBHjEq7EO4eowASbABJiAaxNgweva/cutYwIuQ+DK5cvKVpmNGzd2mTYV1ZAMudMT+b/m4FoEXM6BhjOrmi2XEPE6Xtf6oZVWa9xhHS9tGhEeHg6D3G2sltyDODo62m22zKRnQsuWLXHh4kV4yP25T58+jWrVqjl8O/E6XodRlWlCl5vjLVN6JXwxFrYlDNQNinNlhwgHDhxAt27dFIGr7ktML9butE81PROozWr7aY9mEsBbtmyBI77kyWkGP1e09yDgEa/2+oRrxATcmoAqcGn/YNXrEgGh3ZrcabSr3gRZWVlo0aKFsn+4GkcvXLS/saMCWM3Hn9ogwHO82ugHrgUTcHsCJHBpk5OOHTsqOydZCl2C426jXfWGoBG+5RQaxRMb2tyCWBEzYsfBeQi4nOAlYwT1z3m6gWvKBNyXwLfffmdX4BIZGu3Srk3uGqjtxKBgKCiAiSUH7RNwOVWz9pFzDZkAEyACs2fPxltvvYVLly4hLS2tSCi0ZaI7hxMnThTZ/AoVKoD2W37llVcwfvz4ItNzgvIhwMZV5cOdr8oE3J5AcnIyHBEmKqjipFXzuNsnvcDQH7HloF0CLqdq1i7qomvWuUsX0BpF+iODCg5MoCgCkydPNt8zNIJ0pjBx4kRclqPd6dPfdKZqa7quxJKYElsKdE+ozxS6VzhogwCPeLXRD0otDsn1iWQwQUHINYscmEBRBC7K9Z3qSDAlJaWo5Jo6r25XN3XqM5j0yMPYt38/Bg4caLOODeRSmu3bttk878on6KU8NjbWZhNXrVqFNq1bo0JwcL7lQ3RPqPdHZGSkzfx8omwJsOAtW958NSbABAoQoHWm9Ne3b19ltGZLAHt5eaFa9eoFcrvHIbXdWlAFbuUqVUBrdjk4BwFWNTtHP3EtmYDLEyDBQYJVFcAkVCwDjdwGDx5sGeUW36nN6qhVbTCxIZUysSJmLHRVMs7xaf01yjnqbrWWw4cPN8cvWbLE/J2/MAEm4BwEVAHcs2dP7NmzB1evXjWroE+ePOkcjSjBWlq2mQRu1apVQWpj9khVgpDLuCiXE7xLly4tY4R8OSbABEqDAAmWtm3bgvwNqwL4Djn6IyOhr776qjQuqbkyx40bh9OnTkEVuOQmkke3muumYlfI5dbxWnp4cTYDJfI+Qw8ZCvTA4cAEiiJAKkh1DWztWrVceg6Ufhv0GyF3ic2bNy8KjUucV58JNytwaUen8xcuKCxoja+7r4XWyk3BglcrPcH1YAJMgAkwAbcgwMZVbtHN3EgmwASYABPQCgEWvFrpCa4HE2ACTIAJuAUBFrxu0c3cSCbABJgAE9AKAZezav7ss8+0wpbrwQSYABNgAkygEAGXM64q1EKOYAJMgAkwASagIQKsatZQZ3BVmAATYAJMwPUJuJyq2fW7jFvIBFyfQGZmJgx2Ngrxlr6LaT0vBybgjAR4xOuMvcZ1ZgIuSECv1+PFl15SPDPRzkVBgYE2/3x9fXHs2DEXpMBNcgcCPOJ1h17mNjIBJyAwduxYHD58GK+88goqVaqk1PiPP/5A165dUUt65bIMYWFhaNq0qWUUf2cCTkOAjaucpqu4okzAdQnMmDEDCYmJeOP11+HhcUMR11ruMbtlyxYEytEvBybgKgR4xOsqPcntYAJOSkAvfTDTDjyff/55vhbExcUhIyPDIaG7bNky5OTkgFTQ5NM5KysLQUFBuOOOO/KVSb6Pjxw5Aj8/P5Bf9+pyS70ucpN5WyE3Nxfr1q3DypUrQfPONK8cWrkyuslR+MCBA21lKxRPfuPJZ3Kd2rXznVuzZg1os3qqN10rOztbKTc0NFRJt2PHDsTGxoJU7xSoXZFypN+iZUvlmP79888/uHLlitImYtBSbqTQpHFj83n+oj0CN14ttVc3rhETYAJuQMBL7sNbUOhSs9esWYsePXo4RKBBgwaKUBo6dCgee+wxVJEbw4eHhxfKSzse3XfffXjyySdx6NAhVKtWrVAaNWLr1q3o2LEjLsl9b59++ml89913+OKLLzBFlv/LL7/gzjvvVLYsVNPb+3xj+nQ8O3VqoSQk+FevXg3aznTevHmoU6eO8sKgJqwuVeqJUhNA56fK/KSCD6tRQz2tfFIbSCU/YcIEJCenoKpsOweNE5BvYi4cDCInPUUkJlwSctNo01+CuJqSIbL0LtxsbhoTcAECgwYNElLQOdwSOTIV8nErPvjgA6t50tPTxVNPPSVmzZpl9bwaKUeV4vkXXhByz1tx6tQpNTrfpxxVCzlSFkOGDMkXb+3g33//Veo1evRoa6fFX3/9pZz/+OOPrZ6Xo1nlvL1rvfDii0Iam1nNz5HaI+CyqmaRkYqk69H4++sv8MW+rbh0zEeqoIDchOqo0LsvHnrkIYzqWgO1Aj01/mrE1WMC7kcgNTVVUe++/PLLDjd+06ZNSlpro+S9e/fim2++wauvvoraBdS9BS8wceJE7N+/Hzt37sw3+rRMR/PQL7zwgjISlYITUihanjZ/T0pOxvz58xUDMcstS80J5BcyFKNw/vx55bPgvxUrVihR8iWg4CnlOCYmBjVkGU2aNLF6niO1R8AFVc0CWQmXcei9BzCwei88/g0QPvlvHDx6HMePH8f2Zb3Q4d/X8Vz/wRjx0yacTTfuf6u9ruEaMQH3JUDzlhSaNWvmMATaLJ6EW7t27cx5DAYDPvnkE5DamARvUUJ39uzZmDNnDr7//nubQlctXLWq3iyNv2yF16ZNA6mZbQldyqcKXprTLhhIzUxz0lTv41LAWgtkmEbqdQ5OREB7g/BbqZFBZCT8Kz6MgFTNeAuMniZWnS1cXuKPt4nICjrhgRZi3MrzIoHVzoUhcQwTKEcCcr5S1K1b1+EayBGyoo4dMGCAOc+ZM2fEuHHjRHR0tDnO3pcTJ04IOZIVd951l71k5nOxsnz5qBekErcWfvrpJ0FqZgrdunUTY8aMsZZM5Or1Sjlt2rQpdP65554TCQkJonfv3koaaYiVL42cFzZfI98JPtA0ARca8eqRmbgFX3TugWdPAMEeL2HR/DcwoG7ht6CQ/mPRs6q3PBGNOY9+hW0JWTAUTsYxTIAJlAMBsnIm46WePXs6fHVSC1Po16+f8jl37lxlnS+Nghs7aOFLhlM0Qn5g/HiljKL+xZ09qyQJCQkplJS0a/Hx8ejevXuhcwUjyLiMjMFoDbNloDZFRUWBLJzr1aunnCJDLzWQNfSuXbscuoaahz+1QcBlBG9Oyg7M6mYUutB5Y/Cq13GnDcaiZl/0bWFAkA7wOPsX/jqZgwyWvDZocTQTKFsC27dtU5bWtG/f3uELq/O7NM8pDagU9S054rh27Rp+mDXLoXLIaplCVzvLiywL2rx5s3IoR6qW0UrdSb397LPP5ou3d0D1pqVAtGSJAr0AkLr7gQceUI7J2pmCpeD98KOPIEfESjz/cy4CLiF4865fxaqHu2OK4kFOStPJ6zDX+OJbZG8YcACHj+dCz1O9RbLiBEygLAioo1drRlK2rk8jWwpLly7FNDmvevvtt+OJJ56At7c3XpRGUKpAs5U/LS0N0upZSV9NLvFxJKgCfeTIkfmSv/Puu3jxxRcV15f5Ttg5oOVQFC5fvqx8fvPtt3j88ceV7/Svdm2j4L148aISR8Zf9erWs7scypyZv2iOgPML3txUHPuoCYb/YWQbiP/D7184rqKiXNtOnpJvqTzk1dzdyRVySwKPPvqo4lCjbdu2DrWfLKBJWMt5UHwrBZaq+g0ODsa7UgiSSpYMq+wFdcOFihUr2ktmPkdrb09LK2OyklaFJp1cv349oiIjzaphc4YivtS1UCXTqPaCdLbRSjrCUEPNmsa1uxRP4auvvsLEiQ+pp/nTyQg4+XIiPXKj38GEN5JM2HXw/mIqxhSzE/QxZ5GnJ3WR87+HFLPpnJwJaI4AeWlq2LChw/WieU4KgwcPLpTn0cmT8dprrykjUFomRN6srAXyHNWiRQtIQyxldEyONmyFdOlN65FHHoE0mFLKtky3ZctWxMQcw+LFiy2jsU2qz2mulpx30ItBQYchqrU1zQvPlY403pSW0JZBtXymJUc//vgjHn74YbuW0pZ5+bsGCWja9KuIyuWlJ4glo8mCmf50IgBPiN+LyEOnDeK4+H2otwjWmfKOmi/iU3IcyMlJmAAT0BoBqVpWngHbt2+3WjUp5JTz7733ntXzauTMmTOVdGvXrlWjCn1KlbW45557hPQ4Jc6dO1fovK0I6aLSplUz5VmyZIly7b59+wppGFaoGClwlfMdOnQQ5CyDg3MTcN4hnsiFx4oHzSpm6LyQMf5OB0e7J3Fytwey6FbmwASYgFMTWLhwoVJ/W6ppGumSwwtSC1saJxVs9JQpUxR19WQ5Sk6Wji8KBrk8CZ07d1bcNsqlR0WuCVbzk6EUGU4lJRUuU01Tw+QGkrZGlIJdjTZ/kmtJCoek5TMbVJmxOO0XJ92dSCAv5wC+btXGZFAF+HgMwlMnV+A9o42C/Q45OwPjOz+HOZdylSEvRs1H/A93IiyYlhhxYAJMQOsEaCMEcnZB87s070kOKho1ipDemxrnW4ZEApSWJtFGA15eXspGArTEp3///labSEKSNi7Y9O+/6CPnjGk7QrKMPn78hJwrToZcJ6ws8bGauUAkLYv6+aefcf16mrmODRqES4OoqhgxYkS+1ElJScp2iGSJrQrhfAnkwfPPP694yqJtEjk4NwHnFLzSoApL7odu9FITfU949PwG0RsfQpQj/VFA8Hq+ugvxL7RD1QBpEc2BCTABJsAEmEApEnBK4yp9Zgb+WagKXTm76+2PMa84KHQlzGvLf8HmNL1xtFuKcLloJsAEmAATYAIFCTif4BUZyDo6A6/NVZuiQ4W8SbjLwXW7lOvU4b1Iz1HzAz0jGsr1ezzavUGEvzEBJsAEmEBpEXA6wSukZ5fTK77GNpWINKpKnTTMQaMqMn9eiSVfAqqZgy/ux7CBPgjg6V2VKH8yASbABJhAKRJwMqtmgeysGKlmTjEj0Xn5YsQQxx1m6M6dQIxsda6phOyGEWgmfaWy3DUj5S9MgAkwASZQigSca8QrMpF3chXmH7pBRORex6I7KyDIx7G1Qbq8TFy3cFLlM6YfWvr5gBXNN5jyNybABJgAEyg9Ak4leEVWFmLX/ICtZh6y+o8sR/qMHuYYe1+Exyq87j8CH1ok6tQ4Ar7eTjbwt6g/f2UCTIAJMAHnIuBEgleqmTOPYf3vRifhhFnn7Ye7hveHHe9u+Xvjn9X42UuObXONo2Mf3IPhA3zhz3rm/Jz4iAkwASbABEqNgBMJXumXOe8EDluomYMME3DXIMfZ7Fn6DZL1N9LnDB+KMYF+8L0Rxd+YABNgAkyACZQqAScSvLnQnT2JG1tFeyK9fSRaOzg5K7ABq38wD3bldggtcO+UPggJciIEpXorcOFMgAkwASZQFgScZnKT5nfj1v1+YxmRhxfqjuyHZg5S0m1ehO+yjLsiUBZDvWG4p2VFBDgNAQcbysmYABNgAkxA0wScZriXl5OL2IMnzN6mdJ7eaNusocPWyAeWfoZ4CzVzp+cnoX1FP94IUNO3J1eOCTABJuB6BJxmvJenj8WJ6Bsd4KXviKjGN47tfSM18/KvgRx1xVH4NLw4vAqq8OSuPWx8jgkwASbABEqBgJMIXgED9NBnqwQCkddxOO5ycK/spF8/wFcZyqa9SgHdX3kKnSv7w1Mtjj+ZABNgAkyACZQRAScRvAVoyC3A4BsIRzYTEriI7ctW4nKeqYy6T+K/AysglEe7BaDyIRNgAkyACZQFAecUvB6+MITXQbgDhHS7vsB763RmF5GtnpqK3tXZRaQD6DgJE2ACTIAJlAIBJxG8OrmJdS3UaWQi4CGr7e8HnyKA0Gh37QfvYHuCaXK338f4+Z5aCHGSVhfRPD7NBJgAE2ACTkjAaUSQp1cFhEcVr7o02v3vIuOGCN4Yiqdn3I/mYcUrwwn7lKvMBJgAE2ACGibgNFLIw9cPDfo+iKYEM09aWZ09j3N2wKqj3SNybleHJhgx92M83bQqG1TZYcanmAATYAJMoPQJOI3ghWcQgls/jim9JBRDBrx3rMGKK7YBpS54VhnteiAKo+f+gXeGRaCW87TWdsP4DBNgAkyACTg1AacSRd6VG6LXI3eiLS0tSt6NP/+5YBV+2pkVmPnjHzhSuSPGv/w6Hu3THOEBVpNyJBNgAkyACTCBMiXg+boMZXrFW7iYztMHoQ0bolbqUWzYsRfRF/PQtF5z1AoPhr9SbjIurlqAL759DZ8evROPvT0FT/1nKNqFOujQ+RbqxlmZABNgAkyACThCQCdkcCShdtLI0e6FzVgwbzk2/jIbh3xHo/v9TVFDJ5BXVcB731Vc9qiOJj2GYeDAuqisnYpzTZgAE2ACTIAJwAkFr6nXxFXErViN7ScTcUkOaHWeHtBXroImjbqgW6N6qFiJe5cJMAEmwASYgPYIOK/g1R5LrhETYAJMgAkwgSIJOJVxVZGt4QRMgAkwASbABDROgAWvxjuIq8cEmAATYAKuRYAFr2v1J7eGCTABJsAENE6ABa/GO4irxwSYABNgAq5FgAWva/Unt4YJMAEmwAQ0ToAFr8Y7iKvHBJgAE2ACrkWABa9r9Se3hgkwASbABDROgAWvxjuIq8cEmAATYAKuRYAFr2v1J7eGCTABJsAENE6ABa/GO4irxwSYABNgAq5FgAWva/Unt4YJMAEmwAQ0TuD/AUXuSkvduyCaAAAAAElFTkSuQmCC" width="400" style="display: block; margin: auto;" />

]

We may not be interested in these hypotheses, e.g., `$\tau_{KO}$` and `$\tau_{4W}$` are *conditional* effects *at* a given level of a factor (*simple effects*)
---

## Example 1: nothing is statistically significant, very flat genes

---

## Example 1: nothing is statistically significant, very flat genes

Summary of `lm` for the gene in the left plot on previous slide:

```r
multFit <- lm(gExp ~ gType * devStage, subset(egDat,gene=="1448243_at"))
summary(multFit)$coeff
```

```
##                              Estimate Std. Error    t value     Pr(>|t|)
## (Intercept)                 8.5240000  0.2561305 33.2799114 2.154028e-12
*## gTypeNrlKO                 -0.4336667  0.3912458 -1.1084251 2.913251e-01
*## devStage4_weeks            -0.2532500  0.3622232 -0.6991545 4.989723e-01
*## gTypeNrlKO:devStage4_weeks  0.5504167  0.5331781  1.0323317 3.240804e-01
```

---

## Example 2: statistically significant interaction effect: non-parallel

---

## Example 2: statistically significant interaction effect: non-parallel

Summary of `lm` for the gene in the left plot on previous slide:

```r
multFit <- lm(gExp ~ gType * devStage, subset(egDat,gene=="1434709_at"))
summary(multFit)$coeff
```

```
##                            Estimate Std. Error   t value     Pr(>|t|)
## (Intercept)                 8.58550  0.2215161 38.757897 4.083165e-13
*## gTypeNrlKO                 -1.59250  0.3383715 -4.706366 6.434783e-04
*## devStage4_weeks            -2.22075  0.3132711 -7.088907 2.021975e-05
*## gTypeNrlKO:devStage4_weeks  4.96975  0.4611226 10.777502 3.481389e-07
```

When the interaction effect is significant, the *simple* effects may not agree: compare the genotype effect @E16 with that @4W!

*Main* effects (overall): does genotype have an effect on gene expression? we can't answer this question! it depends (on the level of devStage)! (more later)

---

## Example 3: BALANCED & only genotype @E16 is statistically significant

For simplicity here, I've added a random observation in the NrlKO.E16 group (close to its mean) to have a *balanced* design 
> In *unbalanced* designs the *main* effects are a *weighted* average of the simple effects, and the weights are not easy to interpret (beyond the scope of this course but worth noting the issue!)

```r
egDat<-prDat %>% subset(row.names(prDat) %in%
 c("1447753_at","1431651_at")) %>%
 tibble::rownames_to_column(var = "gene")%>% 
 gather(sidChar, gExp,-gene) %>%
 inner_join(prDes,by="sidChar") %>% 
 mutate(grp=interaction(gType, devStage))

#duplicate sample 6 and add noise to gExp of genes
set.seed(123)
egDat <-egDat %>% subset(sidChar=="Sample_6") %>%
 mutate(sidChar="Sample_r",sidNum="r",
 gExp=gExp+rnorm(2,0,.1)) %>% rbind(egDat) %>% 
 arrange(grp)
```
---

## Example 3: only genotype @E16 is statistically significant: parallel and flat

* The interaction effect is not significant (almost parallel pattern).

* The effect of developmental stage is not significant for WT (almost flat pattern).

---

## Example 3: only genotype @E16 is statistically significant: parallel

```r
multFit <- lm(gExp ~ gType * devStage, subset(egDat,gene=="1447753_at"))
summary(multFit)$coeff
```

```
##                               Estimate Std. Error    t value     Pr(>|t|)
## (Intercept)                 6.47725000 0.04513333 143.513681 8.795702e-21
*## gTypeNrlKO                  0.28699556 0.06382816   4.496378 7.312501e-04
## devStage4_weeks            -0.07675000 0.06382816  -1.202447 2.523805e-01
## gTypeNrlKO:devStage4_weeks -0.09949556 0.09026666  -1.102240 2.919732e-01
```

* There is a genotype effect at E16

* There may be a genotype effect *regardless* of the developmental stage (*main* effect). However, that hypothesis is *not* tested here!!

* How do we test a *main effect*??  
---

# **How** do we test the *main* effects?

The main effect measures the *overall* association between the response and a factor. They are the (weighted) average of an effect over the levels of the other factor

> **Note**: a significant interaction means that the effect of a factor depends on the level of the other one. Thus, main effects may mask interesting results!

---

# Main effects

<big>

`anova()` can be used to test the main effects:

`$$H_0: ((E[Y_{KO,E16}]-E[Y_{wt,E16}])+(E[Y_{KO,4W}]-E[Y_{wt,4W}]))/2=0$$`
> for unbalanced experiments `$H_0: w_1 \text{effect}_{E16}+ w_2 \text{effect}_{4W}=0$`

---

# Main effects

```r
tidy(anova(lm(gExp ~ gType * devStage, plot1Dat)))
```

```
## # A tibble: 4 x 6
## term df sumsq meansq statistic p.value
## <chr> <int> <dbl> <dbl> <dbl> <dbl>
*## 1 gType 1 0.225 0.225 27.6 0.000202
*## 2 devStage 1 0.0640 0.0640 7.86 0.0160 
## 3 gType:devStage 1 0.00990 0.00990 1.21 0.292 
## 4 Residuals 12 0.0978 0.00815 NA NA
```

As we suspected in slide #35, there is a significant genotype effect for this gene (1447753_at), i.e., its mean expression changes in NrlKO group (compared to wt), on average over developmental stages.

`$^*$` Note: `anova` uses type II sums of squares, which follows the principle of marginality, thus order matters in unbalanced designs!

---

# Main & interaction effects: important notes

- A **significant interaction effect** means that the effect of one factor depends on the levels of the other one. 
  - e.g., the effect of genotype depends on developmental stage

- **Main effects**: are the (weighted) average of an effect over the levels of the other factor.

- A **non-significant main effect** means that, on average, there's no evidence of a factor's effect
  - e.g, no evidence of a genotype effect, on average over both developmental stages

- **Note of caution**: if the interaction is significant, it is possible that one or both simple effects are significant but the average effect (i.e., the main effect) is not. This is because the effect of a factor *depends on* the level of the other one!

---
# Additive models

- In some applications, we need to/want to test the interaction term

- However, additive models are easier and smaller

- If there are no statistical or theoretical grounds to include the interaction term, additive models are preferred

- Additive effects: `$E[Y_{NrlKO,4W}]-E[Y_{wt,E16}]=\tau_{KO}+\tau_{4W}$`

```r
addFit <- summary(lm(formula = gExp ~ gType +devStage,plot1Dat))$coeff
addFit
```

```
##                   Estimate Std. Error    t value     Pr(>|t|)
## (Intercept)      6.5021239  0.0394084 164.993346 5.609641e-23
## gTypeNrlKO       0.2372478  0.0455049   5.213675 1.670701e-04
## devStage4_weeks -0.1264978  0.0455049  -2.779872 1.561988e-02
```

`$^*$` gene=1447753_at in table

---

# **Additive models** and balanced designs

- In an additive model, the parameters are **average effects**, over the levels of the other factor. Now, same as in anova()!!

> Note the agreement!! This is gone in unbalanced designs since weights are computed differently! try!!

- TypeIII sum of squares are required for agreement in unbalanced designs (use `car::Anova`), beyond our scope

---

# Parameters in additive models represent main effects

```r
summary(lm(formula = gExp ~ gType + devStage, plot1Dat))$coeff
```

```
##                   Estimate Std. Error    t value     Pr(>|t|)
## (Intercept)      6.5021239  0.0394084 164.993346 5.609641e-23
*## gTypeNrlKO       0.2372478  0.0455049   5.213675 1.670701e-04
## devStage4_weeks -0.1264978  0.0455049  -2.779872 1.561988e-02
```

```r
summary(lm(formula = gExp ~ gType + devStage, plot1Dat))$coeff[2,3]^2
```

```
## [1] 27.18241
```

```r
tidy(anova(lm(gExp ~ gType + devStage, plot1Dat)))
```

```
## # A tibble: 3 x 6
## term df sumsq meansq statistic p.value
## <chr> <int> <dbl> <dbl> <dbl> <dbl>
*## 1 gType 1 0.225 0.225 27.2 0.000167
## 2 devStage 1 0.0640 0.0640 7.73 0.0156 
## 3 Residuals 13 0.108 0.00828 NA NA
```
---

```r
multEst
```

```
##                (Intercept)                 gTypeNrlKO            devStage4_weeks gTypeNrlKO:devStage4_weeks 
##                 6.47725000                 0.28699556                -0.07675000                -0.09949556
```

```r
addEst 
```

```
##     (Intercept)      gTypeNrlKO devStage4_weeks 
##       6.5021239       0.2372478      -0.1264978
```
---
# Factors with multiple levels

We can generalize the regression model to factors with more levels (e.g., E16, P2, P10 and 4W): we just add more dummy variables (and parameters)!

> With interaction

```
##                               Estimate Std. Error    t value     Pr(>|t|)
## (Intercept)                 5.43325000  0.1240289 43.8063081 4.740219e-28
## gTypeNrlKO                  0.25108333  0.1894573  1.3252764 1.954265e-01
## devStageP2                  0.39900000  0.1754034  2.2747562 3.049627e-02
## devStageP6                  0.19525000  0.1754034  1.1131483 2.747868e-01
## devStageP10                 0.92000000  0.1754034  5.2450520 1.283680e-05
## devStage4_weeks             3.96125000  0.1754034 22.5836544 5.952464e-20
## gTypeNrlKO:devStageP2      -0.22583333  0.2581868 -0.8746896 3.889296e-01
## gTypeNrlKO:devStageP6       0.06041667  0.2581868  0.2340037 8.166263e-01
## gTypeNrlKO:devStageP10     -0.20733333  0.2581868 -0.8030361 4.284868e-01
## gTypeNrlKO:devStage4_weeks -0.69333333  0.2581868 -2.6853939 1.185648e-02
```

Note that all the `devStage` parameters are still *simple* effects, but we now have more: one for each level compared to the reference

---

# Factors with multiple levels (cont.)
<big>

> Without interaction: additive

```
##                   Estimate Std. Error    t value     Pr(>|t|)
## (Intercept)     5.52731618 0.11010606 50.1999257 9.574287e-33
## gTypeNrlKO      0.03159559 0.08783425  0.3597183 7.213497e-01
## devStageP2      0.30176103 0.14182289  2.1277315 4.091897e-02
## devStageP6      0.24113603 0.14182289  1.7002617 9.848949e-02
## devStageP10     0.83201103 0.14182289  5.8665498 1.428982e-06
## devStage4_weeks 3.63026103 0.14182289 25.5971450 2.412597e-23
```

Parameters are now *main* effects (on average over the levels of the other factor) but we have more!

Is developmental stage a significant effect? We haven't tested that!!
---

# Simultaneous hypotheses again

### We generally test two types of null hypotheses:
 
.pull-left[
<center>
`$$H_0: \tau_j = 0$$`
vs
`$$H_0: \tau_j \neq 0$$`
for each *j* individually
 
e.g., Is gene A differentially expressed 2 days after birth compared to E16?
`$$H_0: \tau_{P2}=0$$`
 ]
 
.pull-right[
<center>

`$$H_0: \tau_j = 0$$`
 vs
`$$H_0: \tau_j \neq 0$$`
for all *j* at the same time
 
e.g., Is gene A significantly affected by time (`devStage`)?
 
`$$H_0: \tau_{P2}=\tau_{P6}=\tau_{P10}=\tau_{4W}=0$$`
 ]
---
class: middle
 
## *F*-test and overall significance: a deja vu 
<big>
 - the *t*-test in linear regression allows us to test single hypotheses. Those are given in the summary of `lm`
 `$$H_0 : \tau_i = 0$$`
 `$$H_A : \tau_j \neq 0$$`
 - but we often like to test multiple hypotheses *simultaneously*: 
 `$$H_0 : \tau_{P2} = \tau_{P6} = \tau_{P10} = \tau_{4W}=0\textrm{ [AND statement]}$$`
 `$$H_A : \tau_j \neq 0 \textrm{ for at least one j [OR statement]}$$` the *F*-test allows us to test such compound tests
 
---

# Overall effects: compound tests

### With interaction

> `$H_0: \tau_{KO}=0$` (1 df) 
> `$H_0: \tau_{P2}=\tau_{P6}=\tau_{P10}=\tau_{4W}=0$` (at wt!, 4 df)
> `$H_0: \tau_{KOP2}=\tau_{KOP6}=\tau_{KOP10}=\tau_{KO4W}=0$` (4 df)

```r
tidy(anova(lm(gExp~gType*devStage,hitDat)))
```

```
## # A tibble: 4 x 6
## term df sumsq meansq statistic p.value
## <chr> <int> <dbl> <dbl> <dbl> <dbl>
## 1 gType 1 0.0692 0.0692 1.12 2.98e- 1
## 2 devStage 4 71.0 17.8 289. 6.69e-23
## 3 gType:devStage 4 0.689 0.172 2.80 4.44e- 2
## 4 Residuals 29 1.78 0.0615 NA NA
```

Tests of overall effects of a factor controlling for the other one
---

## Overall effects: compound tests (cont.)

### Without interaction

> `$H_0: \tau_{KO}=0$` (1 df) 
`$H_0: \tau_{P2}=\tau_{P6}=\tau_{P10}=\tau_{4W}=0$` (on average!, 4 df)

```r
tidy(anova(lm(gExp~gType+devStage,hitDat)))
```

```
## # A tibble: 3 x 6
## term df sumsq meansq statistic p.value
## <chr> <int> <dbl> <dbl> <dbl> <dbl>
## 1 gType 1 0.0692 0.0692 0.924 3.44e- 1
## 2 devStage 4 71.0 17.8 237. 8.40e-24
## 3 Residuals 33 2.47 0.0749 NA NA
```
Tests of overall effects of a factor controlling for the other one

The `$t$`-test in `lm` and the `$F$`-test (1 df) in `anova` for gType are not equivalent here due to unbalancedness (order matters)
---

# Nested models: These examples are just special cases of nested models 
For example: does development have a significant effect on gene expression?

Compare the models with and without `devStage`!!

**Model 1**: gExp~gType

**Model 2**: gExp~gType + devStage

Mathematically:

**Model 1**: `$Y_{ijk}=\theta + \tau_{KO}x_{KO,ijk} + \varepsilon$`

**Model 2**: `$Y_{ijk}=\theta + \tau_{KO}x_{KO,ijk} + \tau_{P2}x_{P2,ijk}+\tau_{P6}x_{P6,ijk}+\tau_{P10}x_{P10,ijk}+\tau_{4W}x_{4W,ijk}+ \varepsilon$`
 
 `$$H_0: \tau_{P2}=\tau_{P6}=\tau_{P10}=\tau_{4W}=0$$`

The `$x_{DD,ijk}$` are dummy variables (see [math handout](source/SupportingMaterial/math_handout.html))
 
---
# More general!

---

## Nested models in R

```r
addReduced <- lm(gExp ~ gType, data = hitDat)
addFull <- lm(gExp ~ gType+devStage, data = hitDat)
anova(addReduced,addFull)
```

```
## Analysis of Variance Table
## 
## Model 1: gExp ~ gType
## Model 2: gExp ~ gType + devStage
## Res.Df RSS Df Sum of Sq F Pr(>F) 
## 1 37 73.498 
## 2 33 2.473 4 71.024 236.92 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
```

```r
tidy(anova(addFull))
```

---

## Another special case: goodness of fit!

Compare the full *vs* the intercept-only models (compound test)!
`$$H_0: \tau_{KO}=\tau_{P2}=\tau_{P6}=\tau_{P10}=\tau_{4W}=0, \ (5 \text{ df})$$`

```
## Analysis of Variance Table
## 
## Model 1: gExp ~ 1
## Model 2: gExp ~ gType + devStage
## Res.Df RSS Df Sum of Sq F Pr(>F) 
## 1 38 73.567 
## 2 33 2.473 5 71.094 189.72 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
```

```r
summary(addFull)$fstatistic # also given in the summary of lm
```

```
##    value    numdf    dendf 
## 189.7238   5.0000  33.0000
```

---

## Goodness of fit also given in output of `lm`

```r
summary(addFull)
```

```
## Call:
## lm(formula = gExp ~ gType + devStage, data = hitDat)
## 
## Residuals:
## Min 1Q Median 3Q Max 
## -0.80117 -0.12450 -0.03208 0.17062 0.50009 
## 
## Coefficients:
## Estimate Std. Error t value Pr(>|t|) 
## (Intercept) 5.52732 0.11011 50.200 < 2e-16 ***
## gTypeNrlKO 0.03160 0.08783 0.360 0.7213 
## devStageP2 0.30176 0.14182 2.128 0.0409 * 
## devStageP6 0.24114 0.14182 1.700 0.0985 . 
## devStageP10 0.83201 0.14182 5.867 1.43e-06 ***
## devStage4_weeks 3.63026 0.14182 25.597 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.2738 on 33 degrees of freedom
## Multiple R-squared: 0.9664,	Adjusted R-squared: 0.9613 
*## F-statistic: 189.7 on 5 and 33 DF, p-value: < 2.2e-16
```

---

## Summary

- ** *t*-tests** can be used to test the equality of **2** population means

- **ANOVA** can be used to test the equality of **more than 2** population means simultaneously (main effects)

- **Linear regression** provides a general framework for modelling the relationship between a response and different type of explanatory variables

- *t*-tests are used to test the significance of *simple effects* (*individual* coefficients)

- *F*-tests are used to test the significance of *main effects* (*simultaneously* multiple coefficients)

- *F*-tests are used to compare nested models
  - e.g., *overall* effects or *goodness of fit*